Publications Book chapters 2008 [1] Kovács, Sz.: Fuzzy Rule Interpolation, Article in the Encyclopedia of artificial intelligence (Juan Ramon Rabunal Dopico, Julian Dorado de la Calle, and Alejandro Pazos Sierra, editors), Information Science Reference, IGI Global, Hershey, New York, ISBN 978-1-59904-849-9, pp. 728-733, (2008). In journals and periodicals 2009 [1] Dávid Vincze and Szilveszter Kovács: Extending Fuzzy Q-learning with Fuzzy Rule Interpolation Method FIVE, SCIENTIFIC BULLETIN of Politehnica University of Timisoara, ROMANIA, Transactions on AUTOMATIC CONTROL and COMPUTER SCIENCE, Vol. 54 (68), Fasc. 4, 2009, ISSN 1224-600X, pp.173-178, (2009). 2008 [2] Kovács, Sz.: Fuzzy Rule Interpolation from a Practical Point of View, Acta Universitas Jaurinensis, Series Intelligentia Computatorica, Vol. 1, No. 3, ISSN 1789-6932, pp. 595-611, (2008). [3] Johanyák, Zs. Cs., Kovács, Sz.: Polar-cut Based Fuzzy Model for Petrophysical Properties Prediction, Scientific Bulletin of Politehnica University of Timisoara, Romania, Transactions on Automatic Control and Computer Science, Vol: 57 (67), Fascicole 4, ISSN 1224-600X, pp. 195-200, (2008). 1. Berecz, A.: Fuzzy rule interpolation based tool life modeling using RBE-SI and FRIPOC, Proceedings - 2009 5th International Symposium on Applied Computational Intelligence and Informatics, SACI 2009, art. no. 5136223, pp. 11-16, (2009). (Scopus) [4] Johanyák, Zs. Cs., Alvarez Gil, R. P. and Kovács, Sz.: Extending the Polar Cut based set interpolation and Revision Methods to the case of Polygonal and Gaussian Shaped Fuzzy Sets, Annals of the Faculty of Engineering Hunedoara, Tome V, Fascicole 3, ISSN 1584-2673, pp. 191-198, (2008).
[5] Kazuyuki Morioka, Szilveszter Kovács, Péter Korondi, Joo-Ho Lee, Hideki Hashimoto: Adaptive Camera Selection based on Fuzzy Automaton for Object Tracking in a Multi-Camera System, Annals of the Faculty of Engineering Hunedoara, Tome VI, Fascicole 1, ISSN 1584-2665, pp. 25-34, (2008). 2007 [6] Johanyák, Zs. Cs. and Kovács, Sz.: Survey on three single rule reasoning methods, A GAMF Közleményei, Kecskemét, XXI. évfolyam, pp. 75-86, (2006-2007). 1. Krizsán, Z.: Complexity examination of three single rule reasoning methods, Annals of Faculty of Engineering Hunedoara, Tome VI (2008), Fascicule 1, (ISSN 1584 2665), pp. 177-182, (2008). 2006 [7] Johanyák, Zs. Cs., Kovács Sz.: Fuzzy Set Approximation by Weighted Least Squares regression, Annals of the Faculty of Engineering Hunedoara, Tome IV, Fascicole 1, ISSN 1584-2665, pp. 27-34, (2006). 1. Krizsán, Z.: Uniform Complexity of Feat-p and Feat-ls Fuzzy Set Interpolation Method, MicroCAD 2008, International Scientific Conference, Section N:Applied Information Engineering, 20-21 March 2008, Miskolc, pp. 83-88, (2008). [8] Kovács, Sz.: Extending the Fuzzy Rule Interpolation "FIVE" by Fuzzy Observation, Advances in Soft Computing, Computational Intelligence, Theory and Applications, Bernd Reusch (Ed.), Springer Germany, ISBN 3-540-34780-1, pp. 485-497, (2006). 1. Johanyák, Zs. Cs.: Vague Environment Based Set Interpolation, A GAMF Közleményei, Kecskemét, XXI. évfolyam (2006-2007), pp. 33-44. 2. Johanyák, Zs. Cs., Berecz, A.: Négy egylépéses fuzzy szabályinterpolációs módszer áttekintése, (in Hungarian), AGTEDU 2008, A Magyar Tudomány Ünnepe alkalmából rendezett tudományos konferencia kiadványa, Bács-Kiskun Megyei Tudományos Fórum, Kecskemét, november 6., ISSN: 1586-846x, pp. 269-274, (2008). 3. Johanyák, Zs. Cs., Szabó, A.: Tool life modelling using RBE-DSS method and LESFRI inference mechanism, A GAMF Közleményei, Kecskemét, XXII., pp. 5-16, (2008).
4. Johanyák, Zs. Cs.: Sparse Fuzzy Model Identification Matlab Toolbox - RuleMaker Toolbox, IEEE 6th International Conference on Computational Cybernetics, November 27-29, Stara Lesná, Slovakia, pp. 69-74, (2008) 5. Gál, L., Kóczy, L.T.: Advanced Bacterial Memetic Algorithms, Acta Technica Jaurinensis, Series Intelligentia Computatorica, Vol. 1. No. 3., pp. 225-243, (2008). 6. Johanyák, Zs. Cs.: Fuzzy set teheory based student evaluation, IJCCI 2009 - International Joint Conference on Computational Intelligence, ICFC 2009 - International Conference on Fuzzy Computation, 5-7 October, Funchal-Madeira, Portugal, ISBN: 978-989-674-014-6, pp. 53-58, (2009). 7. Johanyák, Zs. Cs.: Survey on Three Fuzzy Inference Based Student Evaluation Methods, Proceedings of the 10th International Symposium of Hungarian Researchers CINTI 2009, November 12-14, Budapest, pp. 185-192, (2009). 8. Johanyák, Zs. Cs., Berecz, A.: Survey on Practical Applications of Fuzzy Rule Interpolation, Proceedings of the 1st International Scientific and Expert Conference TEAM 2009, December 10-11, Slavonski Brod, pp. 205-213, (2009). 9. Johanyák, Zs. Cs., Ádámné, A.M.: Mechanical Properties Prediction of Thermoplastic Composites using Fuzzy Models, SCIENTIFIC BULLETIN of Politehnica University of Timisoara, ROMANIA, Transactions on AUTOMATIC CONTROL and COMPUTER SCIENCE, ISSN 1224-600X, Vol: 54(68) No: 4/ 2009, pp. 185-190, (2009). 10. Johanyák, Z.C., Ádámné, A.M.: Fuzzy modeling of the relation between components of thermoplastic composites and their mechanical properties, Proceedings - 2009 5th International Symposium on Applied Computational Intelligence and Informatics, SACI 2009, art. no. 5136296, pp. 481-486, (2009). (Scopus) 11. Botzheim, J., Gál, L., Kóczy, L.T.: Fuzzy rule base model identification by bacterial memetic algorithms, Studies in Computational Intelligence, Volume 222, Springer-Verlag Berlin Heidelberg, pp. 21-43, (2009). (Scopus) 12. Johanyák, Z.C.: Sparse fuzzy model identification Matlab toolox - Rulemaker toolbox, ICCC 2008 - IEEE 6th International Conference on Computational Cybernetics, Proceedings, art. no. 4721381, pp. 69-74, (2008). (Scopus) [9] Johanyák, Zs. Cs., Kovács Sz.: Fuzzy Rule Interpolation Based on Polar Cuts, Advances in Soft Computing, Computational Intelligence, Theory and Applications, Bernd Reusch (Ed.), Springer Germany, ISBN 3-540-34780-1,. pp. 499-511, (2006).
1. Krizsán, Z.: Complexity examination of three single rule reasoning methods, Annals of Faculty of Engineering Hunedoara, Tome VI (2008), Fascicule 1, (ISSN 1584 2665), pp. 177-182, (2008). 2. Krizsán, Z.: Uniform Complexity of Feat-p and Feat-ls Fuzzy Set Interpolation Method, MicroCAD 2008, International Scientific Conference, Section N:Applied Information Engineering, 20-21 March 2008, Miskolc, pp. 83-88, (2008). 3. Drenyovszki, R.: Távolságmértékek a fuzzy szabály-interpolációban, XIII. Fiatal Mőszakiak Tudományos Ülésszaka, Kolozsvár, 2008. március 14-15, pp. 69-72, (in Hungarian), (2008). 4. Gál, L., Kóczy, L.T.: Advanced Bacterial Memetic Algorithms, Acta Technica Jaurinensis, Series Intelligentia Computatorica, Vol. 1. No. 3., pp. 225-243, (2008). 5. Berecz, A.: Fuzzy rule interpolation based tool life modeling using RBE-SI and FRIPOC, Proceedings - 2009 5th International Symposium on Applied Computational Intelligence and Informatics, SACI 2009, art. no. 5136223, pp. 11-16, (2009). (Scopus) 6. Botzheim, J., Gál, L., Kóczy, L.T.: Fuzzy rule base model identification by bacterial memetic algorithms, Studies in Computational Intelligence, Volume 222, Springer-Verlag Berlin Heidelberg, pp. 21-43, (2009). (Scopus) [10] Johanyák, Zs. Cs., Kovács Sz.: Survey on various interpolation based fuzzy reasoning methods, Production Systems and Information Engineering Volume 3, HU ISSN 1785-1270, pp. 39-56, (2006). [11] Johanyák, Zs. Cs., Kovács Sz.: A brief survey and comparison on various interpolation based fuzzy reasoning methods, Acta Polytechnica Hungarica, Vol. 3, No. 1, ISSN 1785-8860, pp. 91-105, (2006). 1. Lior Shamir: A proposed stereo matching algorithm for noisy sets of color images, Computers & Geosciences ISSN:0098-3004, Volume 33, Issue 8, August 2007, pp. 1052-1063. (Science Direct) 2. Krizsán, Z.: Complexity examination of three single rule reasoning methods, Annals of Faculty of Engineering Hunedoara, Tome VI (2008), Fascicule 1, (ISSN 1584 2665), pp. 177-182, (2008). 3. C. Pozna, R.-E. Precup, S. Preitl, E. M. Petriu, J. K. Tar: Structure for Behaviourist Representation of Knowledge, Proceedings of 10th International Symposium of Hungarian Researchers in Computational Intelligence and Informatics CINTI 2009, Budapest, Hungary, 2009, pp. 55-68, ISBN 978-963-7154-97-6, (2009).
2005 [12] Johanyák, Zs. Cs., Kovács Sz.: Neuro-fuzzy módszerek alkalmazása a kísérletmódszertanban, A GAMF Közleményei, Kecskemét, XX. Évfolyam, ISSN 0230-6182, (in Hungarian), pp. 37-48, (2005). [13] Sz. Kovács: Interpolative Fuzzy Reasoning in Behaviour-based Control, Advances in Soft Computing, Vol. 2, Computational Intelligence, Theory and Applications, Bernd Reusch (Ed.), Springer, Germany, ISBN 3-540-22807-1, pp.159-170, (2005). [14] Sz. Kovács: Interpolation-based Fuzzy Reasoning as an Application Oriented Approach, Acta Polytechnica Hungarica, Journal of Applied Sciences at Budapest Tech Hungary, Special Issue on Computational Intelligence, Guest Editor: Imre J. Rudas, Vol. 2, No 1, Budapest, Hungary, ISSN 1785-8860, pp.93-107, (2005). 1. Johanyák, Zs. Cs.: Vague Environment Based Set Interpolation, A GAMF Közleményei, Kecskemét, XXI. évfolyam (2006-2007), pp. 33-44. 2004 [15] Sz. Kovács: Interpolation-based Fuzzy Reasoning in Behaviour-based Control Structures, Production Systems and Information Engineering, A publication of the University of Miskolc, Hungary, Vol. 2, HU ISSN 1785-1270, pp.53-71, (2004). [16] Zs. Cs. Johanyák, Sz. Kovács: A fuzzy tagsági függvény megválasztásáról, A GAMF Közleményei, Kecskemét, XIX. évfolyam, ISSN 0230-6182, (in hungarian), pp. 73-84, (2004). 2003 [17] Sz. Kovács, P.Baranyi: Fuzzy Q-learning in SVD Reduced Dynamic State-space, Production Systems and Information Engineering, A publication of the University of Miskolc, Hungary, Vol. 1, HU ISSN 1785-1270, pp.107-124, (2003). [18] Masaharu Sugiyama, Munehiro Goto, Szilveszter Kovács, Tadahiro Matsumoto, Tohru Naoi: A Cropping-Robust Watermarking Method Based on Singular Value Decomposition and Haar Transformation, Systems and Computers in Japan, Vol. 34, No. 9, pp. 38-46, (Translated from Denshi Joho Tsushin Gakkai Ronbunshi, Vol. J85-D-II, No. 5, May 2002, pp. 877-885.), (2003).
1. Alessandro Basso, Francesco Bergadano, Davide Cavagnino, Victor Pomponiu and Annamaria Vernone: A Novel Block-based Watermarking Scheme Using the SVD Transform, Algorithms 2009, vol. 2; doi:10.3390/a2010046, www.mdpi.com/journal/algorithms, ISSN 1999-4893, pp. 46-75, (2009). 2001 [19] Sz. Kovács: SVD Reduction in Continuos Environment Reinforcement Learning, Lecture Notes in Computer Science, Vol. 2206, Computational Intelligence, Theory and Applications, Bernard Reusch (Ed.), Springer, ISBN 3-540-42732-5, pp.719-738, Germany, (2001). IF (Lect Notes Comput SC, 2001): 0,415 1999 [20] Sz. Kovács: Similarity Based System Reconfiguration by Fuzzy Classification and Hierarchical Interpolate Fuzzy Reasoning, Lecture Notes in Computer Science, Vol. 1625, Bernard Reusch (Ed.), Springer, pp.12-19, Germany, (1999). IF (Lect Notes Comput SC, 1999): 0,872 1. Pan, W., Tang, Y., Xu, Y., Qin, K.: Local relations hold reasoning, Proceedings of the IEEE International Conference on Systems, Man and Cybernetics 4, pp. 2151-2156, (2001). (Scopus) [21] Kovács, Sz., Kóczy, L.T.: Application of an approximate fuzzy logic controller in an AGV steering system, path tracking and collision avoidance strategy, Fuzzy Set Theory and Applications, Tatra Mountains Mathematical Publications, Mathematical Institute Slovak Academy of Sciences, Vol.16, pp. 456-467, Bratislava, Slovakia, (1999). 1. Johanyák, Zs. Cs.: Vague Environment Based Set Interpolation, A GAMF Közleményei, Kecskemét, XXI. évfolyam (2006-2007), pp. 33-44. 2. Johanyák, Zs. Cs., Parthiban, R, and Sekaran, G.: Fuzzy Modeling for an Anaerobic Tapered Fluidized Bed Reactor, SCIENTIFIC BULLETIN of Politehnica University of Timisoara, ROMANIA, Transactions on AUTOMATIC CONTROL and COMPUTER SCIENCE, ISSN 1224-600X, Vol: 52(66) No: 2 / 2007, pp.67-72. 3. Johanyák, Zs. Cs., Berecz, A.: Négy egylépéses fuzzy szabályinterpolációs módszer áttekintése, (in Hungarian), AGTEDU 2008, A Magyar Tudomány Ünnepe alkalmából rendezett tudományos konferencia kiadványa, Bács-Kiskun Megyei Tudományos Fórum, Kecskemét, november 6., ISSN: 1586-846x, pp. 269-274, (2008).
4. Johanyák, Zs. Cs., Szabó, A.: Tool life modelling using RBE-DSS method and LESFRI inference mechanism, A GAMF Közleményei, Kecskemét, XXII., pp. 5-16, (2008). 5. Johanyák, Zs. Cs. and Alvarez Gil, R. P.: Generalization of the single rule reasoning method SURE-LS for the case of arbitrary polygonal shaped fuzzy sets, Annals of the Faculty of Engineering Hunedoara, Tome VI (2008), Fascicule 2, pp. 161-170, (2008). 6. Shigeru Kato, Kok Wai Wong: The Automated Guided Vehicle Using Fuzzy Control and CBR Techniques, Proceedings of the Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems (SCIS & ISIS 2008), September 17-21, Nagoya University, Nagoya, Japan, SU-C1-1, pp. 1788-1792, (2008). 7. Johanyák, Zs. Cs., Berecz, A.: Survey on Practical Applications of Fuzzy Rule Interpolation, Proceedings of the 1st International Scientific and Expert Conference TEAM 2009, December 10-11, Slavonski Brod, pp. 205-213, (2009). 8. Kato, S., Wong, K.W.: Intelligent automated guided vehicle with reverse strategy: A comparison study, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5506 LNCS (PART 1), pp. 638-646, (2009). (Scopus) 1997 [22] Kovács, Sz., Kóczy, L.T.: Application of the Approximate Fuzzy Reasoning Based on Interpolation in the Vague Environment of the Fuzzy Rulebase in the Fuzzy Logic Controlled Path Tracking Strategy of Differential Steered AGVs, Computational Intelligence - Theory and Applications, Lecture Notes in Computer Science, 1226, Springer, pp.456-467, Germany, (1997). 1. Baranyi P., Varkonyi-Koczy A. R., Yam Y., Patton R.J.: Adaptation of TS fuzzy models without complexity expansion: HOSVD-based approach, IEEE Transactions on Instrumentation and Measurement, 54 (1): 52-60 Feb. 2005. (SCI) (Scopus) 2. Baranyi P., Yam Y., Varkonyi-Koczy A. R., Patton R.J.: SVD-based reduction to MISO TS models, IEEE Transactions on Industrial Electronics, 50 (1): 232-242 Feb. 2003. (SCI) (Scopus) 3. Baranyi, P., Varkonyi-Koczy, A. R.: Adaptation of SVD-based fuzzy reduction via minimal expansion, IEEE Transactions on Instrumentation and Measurement, 51 (2): 222-226 Apr. 2002. (SCI) (Scopus)
4. Tikk, D.: Investigation of fuzzy rule interpolation techniques and the universal approximation property of fuzzy controllers, Ph.D. dissertation, p. 105, Technical University of Budapest, Faculty of Electrical Engineering and Informatics, Department of Telecommunications and Telematics, Budapest, 1999. 5. Zhiheng Huang and Qiang Shen: Fuzzy Interpolation and Extrapolation: A Practical Approach, IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 16, NO. 1, FEBRUARY, pp. 13-28, (2008). 6. Shigeru Kato, Kok Wai Wong: The Automated Guided Vehicle Using Fuzzy Control and CBR Techniques, Proceedings of the Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems (SCIS & ISIS 2008), September 17-21, Nagoya University, Nagoya, Japan, SU-C1-1, pp. 1788-1792, (2008). 7. Johanyák, Zs. Cs., Berecz, A.: Survey on Practical Applications of Fuzzy Rule Interpolation, Proceedings of the 1st International Scientific and Expert Conference TEAM 2009, December 10-11, Slavonski Brod, pp. 205-213, (2009). [23] Kovács, Sz., Kóczy, L.T.: The use of the concept of vague environment in approximate fuzzy reasoning, Fuzzy Set Theory and Applications, Tatra Mountains Mathematical Publications, Mathematical Institute Slovak Academy of Sciences, vol.12., pp.169-181, Bratislava, Slovakia, (1997). 1. Tikk, D.: Notes on the approximation rate of fuzzy KH interpolators, International journal, Fuzzy Sets and Systems, Volume 138, Issue 2, 1 September 2003, Pages 441-453. (Scopus) 2. Leila Muresan: Interpolation in Hierarchical Fuzzy Rule Bases, MFT Periodika 2001-03. Hungarian Society of IFSA, Hungary, 2001. www.mft.hu 3. Tikk, D.: Investigation of fuzzy rule interpolation techniques and the universal approximation property of fuzzy controllers, Ph.D. dissertation, p. 105, Technical University of Budapest, Faculty of Electrical Engineering and Informatics, Department of Telecommunications and Telematics, Budapest, 1999. 4. Zhiheng Huang: Rule Model Simplification, Ph.D. dissertation, p. 221, School of Informatics, University of Edinburgh, (2006). 1995 [24] Kóczy, L.T., Kovács, Sz.: Shape of the fuzzy conclusion generated by linear interpolation of trapezoidal If... then rules, Fuzzy Set Theory and its Applications, Tatra Mountains Mathematical Publications, Mathematical Institute Slovak Academy of Sciences, vol.6., pp.83-93, Bratislava, Slovakia, (1995).
1994 [25] Kóczy, L.T., Kovács, Sz.: The convexity and piecewise linearity of the fuzzy conclusion generated by linear fuzzy rule interpolation, BUSEFAL, automne, pp.23-29, URA-CNRS, Université Paul Sabatier, Toulouse, France, (1994). 1. D. Tikk, P. Baranyi: Comprehensive analysis of a new fuzzy rule interpolation method, IEEE Trans. on Fuzzy Systems, 8(3):281-296, 2000. 2. Wong, K.W., Gedeon, T.D., Fung, C.C.: Using Modified Alpha-cut Based Fuzzy Interpolation in Petrophysical Properties Prediction, Proceedings of the 4-th Japan-Australia Joint Workshop on Intelligent and Evolutionary Systems, October 2000, Hayama, Japan, 31 Oct-2 Nov, pp. 136-142. (2000). 3. Wong, K.W., Gedeon, T.D., and Tikk, D.: An Improved Multidimensional Alpha-cut Based Fuzzy Interpolation Technique, International Conference on Artificial Intelligence in Science and Technology 2000, December 2000, Hobart, Australia. 4. K.W. Wong, T.D. Gedeon: Petrophysical properties prediction using self-generating fuzzy rules inference system with modified alpha-cut based fuzzy interpolation. Proc. of the 7th Int. Conf on Neural Information Processing (ICONIP 2000), Taejon, Korea, November 2000, pp. 1088-1092. 5. Tikk, D.: Investigation of fuzzy rule interpolation techniques and the universal approximation property of fuzzy controllers, Ph.D. dissertation, p. 105, Technical University of Budapest, Faculty of Electrical Engineering and Informatics, Department of Telecommunications and Telematics, Budapest, 1999. 6. Zhiheng Huang: Rule Model Simplification, Ph.D. dissertation, p. 221, School of Informatics, University of Edinburgh, (2006). [26] Kovács, Sz., Kóczy, L.T.: Approximation of the incomplete fuzzy rulebase based on the vague environment of the fuzzy rulebase, (in Hungarian), GÉP Technical Journal of the Hungarian Machine Industrial Association, XLVIII, 1996/2, pp.12-14, (1996). In conference proceedings 2009 [1] Kovács, Sz., Vincze, D., Gácsi, M., Miklósi, Á., Korondi, P.: Interpolation based Fuzzy Automaton for Human-Robot Interaction, Preprints of the 9th International Symposium on Robot Control (SYROCO'09), The International Federation of Automatic Control (IFAC), Nagaragawa Convention Center, Gifu, Japan, September 9-12, pp.451-456, (2009)
2008 [2] Kovács, Sz.: Fuzzy Rule Interpolation in a Practical Point of View, Abstracts of the First Gyır Symposium on Computational Intelligence, 23 September 2008, Hungary, pp.42-44, (2008) [3] Kazuyuki Morioka, Szilveszter Kovács, Joo-Ho Lee, Péter Korondi, Hideki Hashimoto: Fuzzy-Based camera Selection for Object Tracking in a Multi-Camera System, Proceedings of Conference on Human System Interaction (HSI'08), ISBN 1-4244-1543-8, May 25-27, 2008, Krakow, Poland, pp.767-772, (2008). [4] Krizsán, Z., Kovács, Sz.: Gradient based parameter optimisation of FRI FIVE, Proceedings of the 9th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, Budapest, Hungary, November 6-8, ISBN 978-963-7154-82-9, pp. 531-538, (2008). [5] Vincze, D., Kovács, Sz.: Applying Fuzzy Rule Interpolation for the Task of Controlling Guidance and Obstacle Avoidance Behaviour of a Robot, Proceedings of the 9th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, Budapest, Hungary, November 6-8, ISBN 978-963-7154-82-9, pp. 229-241, (2008). [6] Vincze, D., Kovács, Sz.: Using fuzzy rule interpolation based automata for controlling navigation and collision avoidance behaviour of a robot, IEEE 6th International Conference on Computational Cybernetics, November 27-29, Stara Lesná, Slovakia, pp. 79-84, (2008). 1. Johanyák, Zs. Cs., Berecz, A.: Survey on Practical Applications of Fuzzy Rule Interpolation, Proceedings of the 1st International Scientific and Expert Conference TEAM 2009, December 10-11, Slavonski Brod, pp. 205-213, (2009). 2007 [7] Kazuyuki MORIOKA, Yudai OINAGA, Szilveszter KOVÁCS, Péter KORONDI: Communication Among Multiple Cameras in Object Tracking System, SICE System Integration Conference 2007 (in Japanese), pp.1268-1269, (2007). [8] Johanyák, Zs. Cs., Kovács, Sz.: Fuzzy modeling of Petrophysical Properties Prediction Applying RBE-DSS and LESFRI, International Symposium on Logistics and Industrial Informatics (LINDI 2007), September 13-15, 2007, Wildau, Germany, pp.87-92, (2007).
[9] Johanyák, Zs. Cs., Kovács, Sz.: Fuzzy rendszer generálása szabálybázis bıvítéssel, (in Hungarian), AGTEDU 2007, 2007 november 8, Kecskemét, ISSN: 1586-846x, pp. 241-246, (2007) [10] Johanyák, Zs. Cs., Kovács, Sz.: Sparse Fuzzy System Generation by Rule Base Extension, 11 th IEEE International Conference on Intelligent Engineering Systems, (IEEE INES 2007), 29 June 1 July, Budapest, Hungary, ISBN 1-4244-1148-3, pp. 99-104, (2007). 1. Marius-Lucian Tomescu, Stefan Preitl, Radu-Emil Precup, József K. Tar: Stability Analysis Method for Fuzzy Control Systems Dedicated Controlling Nonlinear Processes, Acta Polytechnica Hungarica, Volume 4, Issue Number 3, (2007). 2. Krizsán, Z.: Uniform Complexity of Feat-p and Feat-ls Fuzzy Set Interpolation Method, MicroCAD 2008, International Scientific Conference, Section N:Applied Information Engineering, 20-21 March 2008, Miskolc, pp. 83-88, (2008). 3. Gál, L., Kóczy, L.T.: Advanced Bacterial Memetic Algorithms, Acta Technica Jaurinensis, Series Intelligentia Computatorica, Vol. 1. No. 3., pp. 225-243, (2008). 4. Precup, R.-E., Preitl, S., Petriu, E.M., Tar, J.K., Tomescu, M.L., Pozna, C.: Generic two-degree-of-freedom linear and fuzzy controllers for integral processes, Journal of the Franklin Institute 346 (10), December 2009, pp. 980-1003, (2009). (Scopus) 5. Precup, R.E., Tomescu, M.L., Preitl, S., Petriu, E.M., Kilyeni, S., Barbulescu, C.: Stability analysis approach to a class of fuzzy controlled nonlinear time-varying systems, IEEE EUROCON 2009, EUROCON 2009, art. no. 5167750, pp. 958-963, (2009). (Scopus) 6. Pozna, C., Precup, R.-E.: Modeling derived from bayesian filtering: Analysis of estimation process, Proceedings - 2009 International Conference on Intelligent Engineering Systems, INES 2009, art. no. 4924740, pp. 73-78, (2009). (Scopus) 7. Berecz, A.: Fuzzy rule interpolation based tool life modeling using RBE-SI and FRIPOC, Proceedings - 2009 5th International Symposium on Applied Computational Intelligence and Informatics, SACI 2009, art. no. 5136223, pp. 11-16, (2009). (Scopus) 8. Radac, M.-B., Precup, R.-E., Preitl, S., Dragos, C.-A.: Iterative feedback tuning in MIMO systems, Signal processing and application, Proceedings - 2009 5th International Symposium on Applied Computational Intelligence and Informatics, SACI 2009, art. no. 5136216, pp. 77-82, (2009). (Scopus)
9. Dragos, C.-A., Preitl, S., Radac, M.-B., Precup, R.-E.: Nonlinear and linearized models and low-cost control solution for an electromagnetic actuator, Proceedings - 2009 5th International Symposium on Applied Computational Intelligence and Informatics, SACI 2009, art. no. 5136218, pp. 89-94, (2009). (Scopus) 10. Rǎdac, M.-B., Precup, R.-E., Preitl, S., Petriu, E.M., Dragoş, C.-A., Paul, A.S., Kilyeni, S.: Signal processing aspects in state feedback control based on iterative feedback tuning, Proceedings - 2009 2nd Conference on Human System Interactions, HSI '09, art. no. 5090950, pp. 40-45, (2009). (Scopus) 11. Botzheim, J., Gál, L., Kóczy, L.T.: Fuzzy rule base model identification by bacterial memetic algorithms, Studies in Computational Intelligence, Volume 222, Springer-Verlag Berlin Heidelberg, pp. 21-43, (2009). (Scopus) 12. Precup, R.-E., Preitl, S., Petriu, E.M., Tar, J.K., Radac, M.-B., Dragos, C.-A.: Stable design of fuzzy controllers for robotic telemanipulation applications, 2009 IEEE Workshop on Computational Intelligence in Virtual Environments, CIVE 2009 - Proceedings, art. no. 4926310, pp. 1-6, (2009). (Scopus) [11] Johanyák, Zs. Cs., Kovács, Sz.: The effect of different fuzzy partition parameterization strategies in gradient descent parameter identification, 4 th IEEE International Symposium on Applied Computational Intelligence and Informatics (IEEE SACI 2007), May 17-18, Timisoara, Romania, ISBN 1-4244-1234-X, IEEE DOI: 10.1109/SACI.2007.375499, pp. 141-146, (2007). 1. Precup, R. E.,Tomescu, M. L. and Preitl, St. : Rule base modification of Takagi-Sugeno fuzzy logic controllers to guarantee system stability, Bulletins for applied & Computer mathematics (PAMM), 25-28 October, 2007, Arad-Oradea, Romania, (2007). 2. Rădac, M.-B., Precup, R.-E., Preitl, S., Tar, J.K., Fodor, J., Petriu, E.M.: Gain-Scheduling and Iterative Feedback Tuning of PI Controllers for Longitudinal Slip Control, IEEE 6th International Conference on Computational Cybernetics, November 27-29, Stara Lesná, Slovakia, pp. 183-188, (2008). 3. Paul, A.S., Precup, R.-E., Fodor, J., Radac, M.-B.: New experimental setups for audio signal processing, Proceedings - 2009 5th International Symposium on Applied Computational Intelligence and Informatics, SACI 2009, art. no. 5136282, pp. 405-410, (2009). (Scopus) 4. David, R.C., Rǎdac, M.-B., Preitl, S., Tar, J.K.: Particle swarm optimization-based design of control systems with reduced sensitivity, Proceedings - 2009 5th International Symposium on Applied Computational Intelligence and Informatics, SACI 2009, art. no. 5136298, pp. 491-496, (2009). (Scopus)
5. Rǎdac, M.-B., Precup, R.-E., Preitl, S., Tar, J.K., Fodor, J., Petriu, E.M.: Gain-scheduling and iterative feedback tuning ofpi controllers for longitudinal slip control, ICCC 2008 - IEEE 6th International Conference on Computational Cybernetics, Proceedings, art. no. 4721402, pp. 183-188, (2008). (Scopus) [12] Johanyák, Zs. Cs., Kovács, Sz.: Vague Environment-based Two-step Fuzzy Rule Interpolation Method, 5 th Slovakian-Hungarian Joint Symposium on Applied Machine Intelligence and Informatics (SAMI 2007), January 25-26, Poprad, Slovakia, ISBN 978 963 7154 56 0, pp. 189-200, (2007). 1. Krizsán, Z.: Complexity examination of three single rule reasoning methods, Annals of Faculty of Engineering Hunedoara, Tome VI (2008), Fascicule 1, (ISSN 1584 2665), pp. 177-182, (2008). 2. Krizsán, Z.: Uniform Complexity of Feat-p and Feat-ls Fuzzy Set Interpolation Method, MicroCAD 2008, International Scientific Conference, Section N:Applied Information Engineering, 20-21 March 2008, Miskolc, pp. 83-88, (2008). 2006 [13] Kovács, Sz., Korondi, P., Hashimoto, H.: Adaptive Personalisation of the Intelligent Space by Fuzzy Automaton, 7 th International Symposium of Hungarian Researchers on Computational Intelligence (HUCI 2006), November 24-25, Budapest. ISBN 963 7154 54 X, pp. 131-141, (2006). [14] Johanyák, Zs. Cs., Kovács, Sz.: Fuzzy Rule Interpolation by the Least Squares Method, 7 th International Symposium of Hungarian Researchers on Computational Intelligence (HUCI 2006), November 24-25, Budapest. ISBN 963 7154 54 X, pp. 495-506, (2006). 1. Krizsán, Z.: Complexity examination of three single rule reasoning methods, Annals of Faculty of Engineering Hunedoara, Tome VI (2008), Fascicule 1, (ISSN 1584 2665), pp. 177-182, (2008). 2. Krizsán, Z.: Uniform Complexity of Feat-p and Feat-ls Fuzzy Set Interpolation Method, MicroCAD 2008, International Scientific Conference, Section N:Applied Information Engineering, 20-21 March 2008, Miskolc, pp. 83-88, (2008). 3. Berecz, A.: Fuzzy rule interpolation based tool life modeling using RBE-SI and FRIPOC, Proceedings - 2009 5th International Symposium on Applied Computational Intelligence and Informatics, SACI 2009, art. no. 5136223, pp. 11-16, (2009). (Scopus) [15] Johanyák, Zs. Cs., Kovács, Sz.: A brief survey on fuzzy set interpolation methods, Doktoranduszok Fóruma, University of Miskolc, November 9, pp. 72-77, (2006).
1. Krizsán, Z.: Uniform Complexity of Feat-p and Feat-ls Fuzzy Set Interpolation Method, MicroCAD 2008, International Scientific Conference, Section N:Applied Information Engineering, 20-21 March 2008, Miskolc, pp. 83-88, (2008). [16] Kovács, Sz.: Fuzzy Rule Interpolation in Practice, Proceedings of the Joint 3rd International Conference on Soft Computing and Intelligent Systems and 7th International Symposium on advanced Intelligent Systems (SCIS & ISIS 2006), September 20-24, 2006, O-okayama Campus West Bldg. 9, Tokyo Institute of Technology, Tokyo, Japan, (invited talk), p.6, (2006). 1. Kato, S., Wong, K.W.: Intelligent automated guided vehicle with reverse strategy: A comparison study, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5506 LNCS (PART 1), pp. 638-646, (2009). (Scopus) [17] Zsolt Csaba Johanyák, Domonkos Tikk, Szilveszter Kovács, Kok Wai Wong: Fuzzy Rule Interpolation Matlab Toolbox FRI Toolbox, Proc. of the IEEE World Congress on Computational Intelligence (WCCI'06), 15th Int. Conf. on Fuzzy Systems (FUZZ-IEEE'06), July 16--21, Vancouver, BC, Canada, pages 1427-1433, Omnipress. ISBN 0-7803-9489-5, (2006). 1. Shyi-Ming Chen, Yuan-Kai Ko: Fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on α-cuts and transformations techniques, IEEE Transactions on Fuzzy Systems, Dec., Volume: 16, Issue: 6, pp. 1626-1648., ISSN: 1063-6706, (2008). (Scopus) 2. Gál, L., Kóczy, L.T.: Advanced Bacterial Memetic Algorithms, Acta Technica Jaurinensis, Series Intelligentia Computatorica, Vol. 1. No. 3., pp. 225-243, (2008). 3. Berecz, A.: Fuzzy rule interpolation based tool life modeling using RBE-SI and FRIPOC, Proceedings - 2009 5th International Symposium on Applied Computational Intelligence and Informatics, SACI 2009, art. no. 5136223, pp. 11-16, (2009). (Scopus) 4. Botzheim, J., Gál, L., Kóczy, L.T.: Fuzzy rule base model identification by bacterial memetic algorithms, Studies in Computational Intelligence, Volume 222, Springer-Verlag Berlin Heidelberg, pp. 21-43, (2009). (Scopus) [18] Johanyák, Zs. Cs., Kovács, Sz.: Fuzzy set approximation based on linguistic term shifting, MicroCad 2006, Miskolc, March 16-17, Section N: Applied Information Engineering, ISBN 963 661 714 7, pp. 123-128, (2006).
[19] Tikk D., Johanyák Zs. Cs., Kovács Sz., Wong, K. K.: Overview of Fuzzy Interpolation Techniques in Multidimensional Spaces, FSTA 2006, 8th International Conference on Fuzzy Set Theory and Applications, Liptovský Ján, Slovak Republic, January 30 - February 3, pp. 104-105, (2006). [20] Johanyák, Zs. Cs., Kovács Sz.: Fuzzy set approximation using polar co-ordinates and linguistic term shifting, SAMI 2006, 4 th Slovakian-Hungarian Joint Symposium on Applied Machine Intelligence, Herl'any, Slovakia, January 20-21, ISBN 963 7154 44 2, pp. 219-227, (2006). 1. Krizsán, Z.: Uniform Complexity of Feat-p and Feat-ls Fuzzy Set Interpolation Method, MicroCAD 2008, International Scientific Conference, Section N:Applied Information Engineering, 20-21 March 2008, Miskolc, pp. 83-88, (2008). 2. Berecz, A.: Fuzzy rule interpolation based tool life modeling using RBE-SI and FRIPOC, Proceedings - 2009 5th International Symposium on Applied Computational Intelligence and Informatics, SACI 2009, art. no. 5136223, pp. 11-16, (2009). (Scopus) [21] Johanyák, Zs. Cs., Kovács, Sz.: Következtetés fuzzy szabálymódosítással, Fiatal Mőszakiak Tudományos Ülésszaka XI., International Scientific Conference, március 24-25, Kolozsvár, ISBN 973-8231-50-7, (in Hungarian), pp. 165-168, (2006). [22] Johanyák, Zs. Cs., Kovács, Sz.: Polár-vágat alapú fuzzy halmaz-interpoláció, Fiatal Mőszakiak Tudományos Ülésszaka XI., International Scientific Conference, március 24-25, Kolozsvár, ISBN 973-8231-50-7, (in Hungarian), pp. 169-172, (2006). [23] Johanyák Zs. Cs., Kovács Sz., Tikk D., K. W. Wong: Fuzzy szabályinterpolációt támogató eljárásgyőjtemény fejlesztése Matlab rendszerben, AGTEDU 2006, november 9, ISSN: 1586-846x, (in Hungarian), pp. 177-182, (2006). 2005 [24] Johanyák Zs. Cs., Kovács Sz.: Fuzzy következtetés sőrő és ritka szabálybázisok esetén, Magyar Tudomány Ünnepe, Bács-Kiskun Megyei Tudományos Fórum, Kecskemét, november.10, ISSN: 1586-846x, (in Hungarian), pp. 201-206, (2005). [25] Johanyák, Zs. Cs., Kovács Sz.: Single Rule Reasoning Methods in Fuzzy Rule Interpolation, Doktoranduszok Fóruma, Miskolci Egyetem, 2005. november 9., pp. 75-80. [26] Johanyák, Zs. Cs., Kovács Sz.: A brief survey and comparison on various interpolation based fuzzy reasoning methods, 6 th International Symposium of Hungarian Researchers on Computational Intelligence, November 18-19, Budapest, ISBN 963 7154 43 4, pp. 323-334, (2005).
[27] Johanyák, Zs., Cs., Kovács, Sz.: Similarity Measurement in Interpolative Fuzzy Reasoning, Proceedings of the 6 th International Carpatian Control Conference, ICCC 2005, May 24-27, Miskolc- Lillafüred, Hungary, Vol. 1, ISBN 963 661 644 2, ISBN 963 661 643 4 ö, pp.317-322, (2005). [28] Johanyák, Zs., Cs., Kovács, Sz.: Interpolation-based Fuzzy Reasoning A Comparison, Proceedings of the microcad 2005 International Scientific Conference, Section N: Applied Information Engineering, March 10-11, Miskolc, Hungary, ISBN 963 661 646 9, ISBN 963 661 660 4, pp.189-194, (2005). [29] Johanyák, Zs., Cs., Kovács, Sz.: Distance based Similarity Measures of Fuzzy Sets, Proceedings of the SAMI 2005, 3rd Slovakian-Hungarian Joint Symposium on Applied Machine Intelligence, January 21-22, Herl any, Slovakia, ISBN 963 7154 35 3, pp. 265-276, (2005). 1. Vít Nováček: A Non-traditional Inference Paradigm for Learned Ontologies, Proceedings of the KWEPSY 2007 Knowledge Web PhD Symposium,Innsbruck, Austria, June 6, 2007, CEUR Workshop Proceedings, ISSN 1613-0073, pp. 57-62, (2007). 2. Drenyovszki, R.: Távolságmértékek a fuzzy szabály-interpolációban, XIII. Fiatal Mőszakiak Tudományos Ülésszaka, Kolozsvár, 2008. március 14-15, pp. 69-72, (in Hungarian), (2008). 2004 [30] Kovács, Sz.: Interpolation-based Fuzzy Reasoning as an Application Oriented Approach, Proceedings of the 5th International Symposium of Hungarian Researchers on Computational Intelligence (SHRCI), November 11-12, Budapest, Hungary, ISBN 963 7154 34 5, pp.359-370, (2004). [31] Sz. Kovács, P.Baranyi: Reduction of the dynamic state-space in Fuzzy Q-learning, Proceedings of the FUZZIEEE, IEEE International Conference on Fuzzy Systems, 25-29 July, Budapest, Hungary, IEEE Catalog Number: 04CH37542C, ISBN: 0-7803-8354-0, p.6, (2004). [32] Sz. Kovács, L. T. Kóczy: Application of Interpolation-based Fuzzy Logic Reasoning in Behaviour-based Control Structures, Proceedings of the FUZZIEEE, IEEE International Conference on Fuzzy Systems, 25-29 July, Budapest, Hungary, IEEE Catalog Number: 04CH37542C, ISBN: 0-7803-8354-0, p.6, (2004).
1. Precup, R.-E., Preitl, Z., Preitl, S., Vaivoda, S., Tar, J.K., Takács, M.: Two-degree-of-freedom fuzzy control in decentralized trajectory tracking, SACI 2007: 4th International Symposium on Applied Computational Intelligence and Informatics - Proceedings, art. no. 4262493, pp. 93-98, (2007). (Scopus) 2. Johanyák, Zs. Cs., Berecz, A.: Survey on Practical Applications of Fuzzy Rule Interpolation, Proceedings of the 1st International Scientific and Expert Conference TEAM 2009, December 10-11, Slavonski Brod, pp. 205-213, (2009). 3. Johanyák, Zs. Cs., Ádámné, A.M.: Mechanical Properties Prediction of Thermoplastic Composites using Fuzzy Models, SCIENTIFIC BULLETIN of Politehnica University of Timisoara, ROMANIA, Transactions on AUTOMATIC CONTROL and COMPUTER SCIENCE, ISSN 1224-600X, Vol: 54(68) No: 4/ 2009, pp. 185-190, (2009). 4. Johanyák, Z.C., Ádámné, A.M.: Fuzzy modeling of the relation between components of thermoplastic composites and their mechanical properties, Proceedings - 2009 5th International Symposium on Applied Computational Intelligence and Informatics, SACI 2009, art. no. 5136296, pp. 481-486, (2009). (Scopus) 5. Cao, H., Si, G., Zhang, Y., Ma, X., Wang, J.: Load control of ball mill by a high precision sampling fuzzy logic controller with selfoptimizing, Asian Journal of Control 10 (6), November 2008, pp. 621-631, (2008). (Scopus) [33] Kovács, Sz.: A Flexible Fuzzy Behaviour-based Control Structure for AGV Control, Proceedings of the microcad 2004 International Scientific Conference, Section G: Automation and Telecommunication, March 18-19, Miskolc, Hungary, ISBN 963 661 608 6, ISBN 963 661 615 9, pp.67-72, (2004). [34] Kovács, Sz.: A Flexible Fuzzy Behaviour-based Control Structure for Adaptive Applications, Proceedings of the SAMI 2004, 2nd Slovakian-Hungarian Joint Symposium on Applied Machine Intelligence, January 16-17, Herl any, Slovakia, ISBN 963 7154 23 X, pp. 119-130, (2004). 2003 [35] Kovács, Sz.: Fuzzy Behaviour-based Structures in Adaptive Applications, Proceedings of the International Conference in Memoriam John von Neumann, December 12, Budapest, Hungary, ISBN 963 7154 21 3, pp.187-198, (2003). [36] Kovács, Sz.: A Flexible Fuzzy Behaviour-based Control Structure, Proceedings of the 4th International Symposium of Hungarian Researchers on Computational Intelligence (SHRCI), November 13-14, Budapest, Hungary, ISBN 963 7154 20 5, pp.129-140, (2003).
[37] Kovács, Sz.: Interpolative Fuzzy Reasoning and Fuzzy Automaton in Behaviour-based Control, Proceedings of the 1st Serbian-Hunagarian Joint Symposium on Intelligent System (SISY), September 19-20, Subotica, Serbia and Montenegro, ISBN 9637154 19 1, pp. 245-255, (2003). [38] Kovács, Sz.: Fuzzy Behaviour-based Control Techniques in Adaptive System Applications, Proceedings of the ICCC 2003, IEEE International Conference on Computational Cybernetics, August 29-31, Siófok, Hungary, ISBN 963 7154 18 3, p. 6, (2003). [39] Chong, A., Gedeon, T.D., Kovács, Sz., Kóczy, L.T.: Sparse Fuzzy Systems Generation and Fuzzy Rule Interpolation: A Practical Approach, Proceedings of the 12th IEEE International Conference on Fuzzy Systems, US, May 25-28, pp. 494-499, vol.1 (2003). [40] Szilveszter Kovács, Péter Baranyi, Tamás D. Gedeon: Model Reduction in User Adaptive Emotion-based Systems, Proceedings of WESIC 2003, 4th Workshop on European Scientific and Industrial Collaboration, May 28-30, Miskolc-Lillafüred, Hungary, ISBN 963 661 570 5, Vol.II, pp. 439-446, (2003). [41] Szilveszter Kovács, Tamás D. Gedeon: Fuzzy Behaviour-based Control Structures in User Adaptive Systems, Proceedings of the microcad 2003 International Scientific Conference, Section I: Automation and Telecommunication, March 6-7, Miskolc, Hungary, ISBN 963 661 547 0, ISBN 963 661 555 1, pp.33-38, (2003). [42] Domonkos Tikk, Szilveszter Kovács, Tamás D. Gedeon, Kok Wai Wong: A feature ranking algorithm for problems with output of continuous range, Proceedings of the SAMI 2003, 1st Slovak-Hungarian Joint Symposium on Applied Machine Intelligence, February 12-14, Herlany, Slovakia, ISBN 963 7154 140, pp.87-103, (2003). [43] Szilveszter Kovács, Péter Baranyi, Tamás D. Gedeon: Model Reduction in User Adaptive Emotion-based Selection Systems, Proceedings of the SAMI 2003, 1st Slovak-Hungarian Joint Symposium on Applied Machine Intelligence, February 12-14, Herl any, Slovakia, ISBN 963 7154 140, pp. 119-130, (2003). 2002 [44] Sz. Kovács, M. Sugiyama: Fuzzy Reasoning and Fuzzy Automata in User Adaptive Emotion-Based Selection, Proceedings of the microcad 2002 International Scientific Conference, Section H: Applied Information Engineering, March 7-8, Miskolc, Hungary, ISBN 963 661 515 2, ISBN 963 661 523 3, pp.125-130, (2002). [45] Sz. Kovács, P. Baranyi: Fuzzy Q-learning in reduced dynamic state-space, Proceedings of the 11th International Workshop on Robotics in Alpe-Adria-Danube Region, June 30 July 2, Budapest, Hungary, ISBN 963 7154 10 8, pp.260-265, (2002).
[46] Sz. Kovács: Fuzzy Reasoning and Fuzzy Automata in User Adaptive Systems, Proceedings of the 18th Hungarian-Korean Seminar on Soft Computing & Computational Intelligence, October 2-3, Budapest, Hungary, ISBN 963 206 066 0, pp.63-72, (2002). [47] Sz. Kovács: Fuzzy Reasoning and Fuzzy Automata in User Adaptive Emotional and Information Retrieval Systems, Proceedings of the 2002 IEEE International Conference on Systems, Man and Cybernetics, October 6-9, Hammamet, Tunisia, 02CH37349C, ISBN: 0-7803-7438-X, WP1N5, p.6, (2002). [48] Sz. Kovács, T. Gedeon: Fuzzy Behaviour-based Control Structures in User Adaptive Systems, Proceedings of the 3rd International Symposium of Hungarian Researchers on Computational Intelligence, November 14-15, Budapest, Hungary, ISBN 963 7154 12 4, pp.147-158, (2002). 2001 [49] Sz. Kovács, M. Sugiyama: The Advantage of SVD Reduction in Continuos Environment Reinforcement Learning, Proceedings of the 11th Soft Science Workshop, March 10-11, Kanazawa, Japan, pp.28-31, (2001). [50] H. Asai, P. Baranyi, Sz. Kovács: Modelling of guiding styles based on generalized neural network (GNN), Proceedings of the 11th Soft Science Workshop, March 10-11, Kanazawa, Japan, pp.36-37, (2001). [51] Sz. Kovács, P. Baranyi, M. Sugiyama: PAL Optics Based Virtual Sensors for Robot Guiding, 1st Workshop on Omnidirectional Vision Applied to Robotic Orientation and Nondestructive Testing (ICAR 01), August 22, Budapest, Hungary, Proc. on CD, (2001). [52] P. Korondi, P. Baranyi, Sz. Kovács, M. Sugiyama: Virtual Training in Telemanipulation, International Conference on Electrical Drivers and Power Electronics (EDPE'01), October 5-7, the High Tatras, Slovakia, pp.403-407, (2001). 1. Péter SZEMES, Zoltán PUKLUS, Károly BÍRÓ: Time Delay Compensation for Internet Based Control, International Conference on Trends and Recent Achievements in Information technology May 16-18, 2002, Cluj-Napoca, Romania, Proceedings pp. 122-127. (2002) 2. Fetyko J., Šimko O.Virtual: Virtual Simulator of Educatioanal Robot International Conference on Electrical Drives and Power Electronics, Proceedings pp. 374-379. 2003.
[53] P. Korondi, A.R. Várkonyi-Kóczy, Sz. Kovács, P. Baranyi, M. Sugiyama: Virtual Training of Potential Function based Guiding Stiles, 9th IFSA World Congress (IFSA 01), pp. 2529-2534, (2001). 1. Hideki Hashimoto, Peter T. Szemes: Ubiquitous Haptic Interface in Intelligent Space, Proceeding of Annual Conference of The Society of Instrument and Control Engineers, Sice03, Aug. 4-6, 2003, Fukui University, Fukui, Japan, pp. 3277-3282, 2003. 2. Peter T. Szemes, Florin Dragan, Emil Voisan, and Hideki Hashimoto: Evaluation of Inhabitant s Walking Habit in Intelligent Space, Proceeding of IEEE/SICE Annual Conference of the IEEE Industrial Electronics Society, Hotel Roanoke and Conference Center, Roanoke Virginia, USA, Nov. 2-6, 2003 3. Peter T. Szemes, Hideki Hashimoto: Estimation of Walking Habit in ispace, International Symposium on Advanced Intelligent Systems, Sept 25-28 Jeju Korea. Proceedings pp. 531-534, 2003 4. Radu-Emil Precup, Stefan Preitl, Csongor Szabó, Zoltán Gyurkó, Peter T. Szemes: Sliding Mode Navigation Control in Intelligent Space, IEEE International Symposium on Intelligent Signal Processing 4-6 September, Budapest, Proceedings pp. 225-230, 2003. 5. Balázs Karlócai, Noémi Csepeli, Antal Szlacsin: Comparison of Navigation Algorithms in Dynamically Changing Environment - A Case Study, Proceedings of Inter Academia Conference vol. 1, pp. 85-91, 2004. 6. Peter T. Szemes, Hideki Hashimoto, Emil Voisan, Florin Dragan: Evaluation of Inhabitant's Walking Habit in Intelligent Space, IECON 2003, pp.1390-1395 7. Peter T. Szemes, Hideki Hashimoto, Csongor Szabo, Florin Dragan: Evaluation of Inhabitant s Walking Habit in Intelligent Space, Sice03, SICE Annual Conference 2003 in Fukui 4-6, August, 2003, Fukui University, Fukui, Japan [54] Sz. Kovács, P. Baranyi: State Space Reduction in Continuous RL, Proceedings of the 2nd International Symposium of Hungarian Researchers on Computational Intelligence, November 12, Budapest, Hungary, ISBN 963 7154 06 X, pp.215-228, (2001). 2000 [55] Sz. Kovács, N. Kubota, K. Fujii and L.T. Kóczy: Behaviour based techniques in user adaptive Kansei technology, Proceedings of the VSMM2000, 6 th International Conference on Virtual Systems and Multimedia, October 3-6, Ogaki, Gifu, Japan, pp.362-369, (2000). [56] Sz. Kovács: Fuzzy Automata in Adaptive System Applications, Proceedings of the SICE2000, SICE Conference on System Integration, December 21-22, Tokyo, Japan, pp.235-236, (2000).
[57] Sz. Kovács: Interpolative Fuzzy Reasoning and Fuzzy Automata in Adaptive System Applications, Proceedings of the IIZUKA2000, 6 th International Conference on Soft Computing, October 1-4, Iizuka, Fukuoka, Japan, pp.777-784, (2000). [58] Sz. Kovács: Similarity based Control Strategy Reconfiguration by Fuzzy Reasoning and Fuzzy Automata, Proceedings of the IECON-2000, IEEE International Conference on Industrial Electronics, Control and Instrumentation, October 22-28, Nagoya, Japan, pp.542-547, (2000). 1. Muhammad Torabi Dashti: A Fuzzy Automaton for Control Applicationstion, Proceedings of the FUZZIEEE, IEEE International Conference on Fuzzy Systems, 25-29 July, Budapest, Hungary, IEEE Catalog Number: 04CH37542C, ISBN: 0-7803-8354-0, p.5, (2004). 2. Shigeru Kato, Kok Wai Wong: The Automated Guided Vehicle Using Fuzzy Control and CBR Techniques, Proceedings of the Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems (SCIS & ISIS 2008), September 17-21, Nagoya University, Nagoya, Japan, SU-C1-1, pp. 1788-1792, (2008). 3. Kato, S., Wong, K.W.: Intelligent automated guided vehicle with reverse strategy: A comparison study, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5506 LNCS (PART 1), pp. 638-646, (2009). (Scopus) [59] Sz. Kovács, G. Terstyánszky, L. T. Kóczy and D. Vadász: Similarity based System Reconfiguration in the control system of an experimental AGV, Proceedings of the SAFEPROCESS 2000, the 4th IFAC Symposium on Fault Detection and Diagnosis Supervision and Safety for Technical Processes, Vol. 1/2, pp.756-761, Budapest, 14-16 June, (2000). [60] Sz. Kovács, N. Kubota, K. Fujii and L.T. Kóczy: Interpolative Fuzzy Reasoning and Fuzzy Automata in Kansei Technology, Proceedings of the AFSS2000, the Fourth Asian Fuzzy Systems Symposium, pp.335-340, May 31-June 3, Tsukuba, Japan, (2000). 1999 [61] Sz. Kovács: Interpolate Fuzzy Reasoning based System Reconfiguration, Proceedings of MicroCAD 99 International Computer Science Conference, pp.194-199, Miskolc, Hungary, 24-25 February, (1999). [62] Sz. Kovács: Similarity Based System Reconfiguration by Fuzzy Classification and Interpolative Fuzzy Reasoning, Proceedings of EUROFUSE-SIC 99, the Fourth Meeting of the EURO Working Group on Fuzzy Sets, pp.538-543, Budapest, Hungary, (1999).
[63] C.T.Yang, P.Baranyi, Y.Yam and Sz.Kovács: Fuzzy Control Identification Using SVD Reduction from Input-output Data in AGV Steering System, Joint Eurofuse-Soft and Intelligent Computing 1999 Conference (EUROFUSE-SIC 99), Budapest, (1999). [64] Sz. Kovács: Interpolate Fuzzy Reasoning Based Fault Classification and System Reconfiguration, Proceedings of IFAC 99, 14th World Congress of International Federation of Automatic Control, p.6, Bejiing, China 05-09 July, Vol. P, CDROM P-7e-05-6, (1999). [65] Sz. Kovács, L.T. Kóczy: Similarity Based System Reconfiguration by Fuzzy Classification and Interpolative Fuzzy Reasoning, Proceedings of WESIC 99, Workshop on Advanced Technologies in Manufacturing, pp.469-476, Newport, United Kingdom, 01-03 September, (1999). [66] Sz. Kovács, L.T. Kóczy: Interpolative Fuzzy Reasoning in Similarity based System Reconfiguration, Proceedings of IEEE SMC 99, IEEE International Conference on Systems, Man, and Cybernetics, Vol. V, pp.226-231, Tokyo, Japan, (1999). 1. Pan, W., Tang, Y., Xu, Y., Qin, K.: Local relations hold reasoning, Proceedings of the IEEE International Conference on Systems, Man and Cybernetics 4, pp. 2151-2156, (2001). (Scopus) [67] Sz. Kovács, Y. Saga, L.T. Kóczy: Interpolative Fuzzy Reasoning in Direct Control Applications, Proceedings of INES 99, IEEE International Conference on Intelligent Engineering Systems, pp.593-598, November 01-03, Poprad, Slovakia, (1999). [68] C.T. Yang, P. Baranyi, Y. Yam, Sz. Kovács: SVD Reduction of a Fuzzy Controller in an AGV Steering System, EFDAN 99, Dortmund, Germany, pp 118-124, (1999). 1. Andras Meinhart: A fuzzy logic control approach to an application of automated guided vehicle, Final Project, Integrated Engineering, Dept. Automation & Precision Engineering and Optics, Technical University of Budapest, Hungary, 1999. 1998 [69] Kovács, Sz., Kóczy, L.T.: Path Tracking and Collision Avoidance Strategy of an AGV Implemented on Interpolation-based Fuzzy Logic Controller, Proceedings of the INES 98 IEEE International Conference on Intelligent Engineering Systems, pp.67-72, Vienna, Austria, (1998).
[70] Kovács, Sz., Kóczy, L. T.: Interpolation based fuzzy logic controllers, as a simplified way for constructing the fuzzy rule base of the path tracking and collision avoidance strategy of an AGV, IEEE International Conference on Systems, Man and Cybernetics, Vol.2, pp. 1317-1322, (1998). 1. Armin Zeinali: Interpolative Fuzzy Inferences Using Least Square Principle, TRANSACTIONS ON ENGINEERING, COMPUTING AND TECHNOLOGY V4 FEBRUARY 2005 ISSN 1305-5313, pp. 245-248. 2. Kiasi, F., Lucas, C., Fazl, A.: An interpolative fuzzy inference using least square principle by means of β-function and high order polynomials, IEEE International Conference on Mechatronics and Automation, ICMA 2005, pp. 545-550, (2005). (Scopus) 3. Lucas, C., Shahmirzadi, D.: An interpolative fuzzy inference procedure using least-square principle, Control and Intelligent Systems 31 (1), pp. 30-36, (2003). (Scopus) [71] Baranyi, P., Martinovics, A., Kovács, Sz., Tikk, D., Yam, Y.: General extension of the fuzzy SVD rule base reduction, IEEE Int. Conf. System Man and Cybernetics (IEEE SMC 98) (invited section), San Diego, California, USA, pp 2785-2790, (1998). 1. Stephen Chi-tin Yang: Fuzzy Rule Base Identification via Singular Value Decomposition, Ph.D. thesis, Dept. Mechanical and Automation Engineering, Chinese University of Hong Kong, (1999). 2. Tikk, D., Wong, K.W.: A feature ranking technique based on interclass separability for fuzzy modeling, ICCC 2007-5th IEEE International Conference on Computational Cybernetics, Proceedings, art. no. 4402044, pp. 251-256, (2007). (Scopus) [72] Kovács, Sz., Bikfalvi, P., Kóczy, L.T.: Application of an Interpolation-based Fuzzy Logic Controller in Path Tracking and Collision Avoidance Strategy of a Vehicle, WESIC 98 Workshop on European Scientific and Industrial Collaboration on promoting Advanced Technologies in Manufacturing, pp.179-183, Girona, Spain, (1998). [73] Kovács, Sz., Kóczy, L.T.: Fuzzy Interpolation - Based Control of an Automatic Guided Vehicle, WACAE 98, Alaska (1998). 1997 [74] Kovács, Sz., Cselényi, J., Pap, L., Ajtonyi, I., Kóczy, L.T.: Path Tracking Strategy of Differential Steered AGVs Implemented on Approximate Fuzzy Logic Controller, Proceedings of the 5 th European Congress on Intelligent Techniques and Soft Computing, pp.1438-1442, Aachen, Germany, (1997).
[75] Kovács, Sz., Kóczy, L.T.: Approximate Fuzzy Reasoning Based on Interpolation in the Vague Environment of the Fuzzy Rulebase as a Practical Alternative of the Classical CRI, Proceedings of the 7 th International Fuzzy Systems Association World Congress (IFSA), pp.144-149, Prague, Czech Republic, (1997). 1. Tikk, D.: Investigation of fuzzy rule interpolation techniques and the universal approximation property of fuzzy controllers, Ph.D. dissertation, p. 105, Technical University of Budapest, Faculty of Electrical Engineering and Informatics, Department of Telecommunications and Telematics, Budapest, 1999. 2. Zhiheng Huang: Rule Model Simplification, Ph.D. dissertation, p. 221, School of Informatics, University of Edinburgh, (2006). [76] Kovács, Sz., Kóczy, L.T.: Approximate Fuzzy Reasoning Based on Interpolation in the Vague Environment of the Fuzzy Rulebase, Proceedings of the INES 97 IEEE International Conference on Intelligent Engineering Systems, pp.63-68, Budapest, Hungary, (1997). 1. Zhiheng Huang: Rule Model Simplification, Ph.D. dissertation, p. 221, School of Informatics, University of Edinburgh, (2006). [77] Cselényi, J., Kovács, Sz., Pap, L., Kóczy, L.T.: Comparing the classical and approximation based fuzzy logic controlled path tracking strategy of automatic guided vehicles, (in Hungarian), MicroCAD 97 International Computer Science Conference, section I, pp.73-82, Miskolc, Hungary, (1997). [78] Kovács, Sz., Ajtonyi, I., Kóczy, L.T.: Study of fuzzy logic control systems based on approximation the vague environment of the fuzzy rulebase, (in Hungarian), MicroCAD 97 International Computer Science Conference, section D, pp.15-18, Miskolc, Hungary, (1997). 1996 [79] Cselényi, J., Kovács, Sz., Pap, L., Kóczy, L.T.: New concepts in the fuzzy logic controlled path tracking strategy of the differential steered AGVs, Proceedings of the 5 th International Workshop on Robotics in Alpe-Adria-Danube Region, pp.587-592, Budapest, Magyarország, (1996). 1. Shigeru Kato, Kok Wai Wong: The Automated Guided Vehicle Using Fuzzy Control and CBR Techniques, Proceedings of the Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems (SCIS & ISIS 2008), September 17-21, Nagoya University, Nagoya, Japan, SU-C1-1, pp. 1788-1792, (2008).
2. Kato, S., Wong, K.W.: Intelligent automated guided vehicle with reverse strategy: A comparison study, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5506 LNCS (PART 1), pp. 638-646, (2009). (Scopus) [80] Kovács, Sz., Kóczy, L.T.: Approximate Fuzzy Reasoning, as Interpolation in the Vague Environment of the Fuzzy Rulebase, Proceedings of the International Panel Conference on Soft and Intelligent Computing, pp.175-180, Budapest, Hungary, (1996). [81] Kovács, Sz.: New Aspects of Interpolative Reasoning, Proceedings of the 6 th. International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), pp.477-482, Granada, Spain, (1996). 1. Alex Chong: Constructing Sparse and Hierarchical Fuzzy Rulebases, Ph.D. Thesis, Murdoch University, School of Information Technology, 2004. p. 180 2. Tikk, D.: Notes on the approximation rate of fuzzy KH interpolators, International journal, Fuzzy Sets and Systems, Volume 138, Issue 2, 1 September 2003, pp. 441-453. (Scopus) 3. Tikk, D.: Investigation of fuzzy rule interpolation techniques and the universal approximation property of fuzzy controllers, Ph.D. dissertation, p. 105, Technical University of Budapest, Faculty of Electrical Engineering and Informatics, Department of Telecommunications and Telematics, Budapest, 1999. 4. Wong, K.W., Tikk, D., Gedeon, T.D., Kóczy, L.T.: Fuzzy rule interpolation for multidimensional input spaces with applications: A case study, IEEE Transactions on Fuzzy Systems 13 (6), pp. 809-819. (2005). (Scopus) [82] Kovács, Sz., Kóczy, L.T.: The use of the concept of vague environment in approximate fuzzy reasoning, Abstracts of the 3 rd Conference on Fuzzy Set Theory and its Applications, pp.36-37, Liptovsky Mikulas, Slovak, (1996). [83] Cselényi, J., Kovács, Sz., Pap, L., Kóczy, L.T.: New results in fuzzy logic controlled path tracking strategy of automatic guided vehicles, (in Hungarian), MicroCAD 96 International Computer Science Conference, section I, pp.63-66, Miskolc, Hungary, (1996). [84] Kovács, Sz., Kóczy, L.T.: Approximation of the incomplete fuzzy rulebase based on the vague environment of the fuzzy rulebase, (in Hungarian), MicroCAD 96 International Computer Science Conference, section D, pp.87-90, Miskolc, Hungary, (1996).
1995 [85] Kovács, Sz., Kóczy, L.T.: Fuzzy Rule Interpolation in Vague Environment, Proceedings of the 3 rd. European Congress on Intelligent Techniques and Soft Computing, pp.95-98, Aachen, Germany, (1995). 1. Tikk, D.: Investigation of fuzzy rule interpolation techniques and the universal approximation property of fuzzy controllers, Ph.D. dissertation, p. 105, Technical University of Budapest, Faculty of Electrical Engineering and Informatics, Department of Telecommunications and Telematics, Budapest, 1999. [86] Kovács, Sz., Kóczy, L.T.: Using Approximate Fuzzy Reasoning for Converting Sparse Rulbase to a Complete One, (in Hungarian), MicroCAD 95 International Computer Science Conference, section D, p.5, Miskolc, Hungary, (1995). [87] Kovács, Sz., Kóczy, L.T.: Simulation of an incomplete fuzzy rulebase based fuzzy logic control of an automatic guided vehicle, (in Hungarian), MicroCAD 95 International Computer Science Conference, section I, pp.51-55, Miskolc, Hungary, (1995). 1994 [88] Kóczy, L.T., Kovács, Sz.: Shape of the fuzzy conclusion generated by linear interpolation in trapezoidal fuzzy rule bases, Proceedings of the 2 nd. European Congress on Intelligent Techniques and Soft Computing, pp.1666-1670, Aachen, Germany, (1994). 1. Tikk, D.: Investigation of fuzzy rule interpolation techniques and the universal approximation property of fuzzy controllers, Ph.D. dissertation, p. 105, Technical University of Budapest, Faculty of Electrical Engineering and Informatics, Department of Telecommunications and Telematics, Budapest, (1999). 2. Shyi-Ming Chen, Yuan-Kai Ko: Fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on α-cuts and transformations techniques, IEEE Transactions on Fuzzy Systems, Dec., Volume: 16, Issue: 6, pp. 1626-1648., ISSN: 1063-6706, (2008). (Scopus) 3. Zhiheng Huang: Rule Model Simplification, Ph.D. dissertation, p. 221, School of Informatics, University of Edinburgh, (2006). [89] Kóczy, L.T., Kovács, Sz.: Linearity and the cnf property in linear fuzzy rule interpolation, Proceedings of the 3 rd IEEE Conference on Fuzzy Systems, volume 2, pp.870-875, Orlando, USA, (1994).
1. R. Palm: Fuzzy Control - Design and Engineering Applications. Chapt. 11 in L.C. Jain (ed.): Soft Computing Techniques in Knowledge-based intelligent Engineering Systems, Physica-Verlag, Heidelberg-New York, pp. 318-385, (1997). 2. Farida Benmakrouha: Construction of a Fuzzy Model with Few Examples, Proceedings of the International Conference, 5th Fuzzy Days, Dortmund, Computational Intelligence - Theory and Applications, Lecture Notes in Computer Science, 1226, Springer, pp.283-293, Germany, (1997). 3. Shimakawa, M., Murakami, S.: Fuzzy prediction model for water demand prediction using an interpolative fuzzy reasoning method, International Journal of Systems Science 34 (14-15), pp. 775-785, (2003). (Scopus) 4. Shimakawa, M., Murakami, S.: Proposal of an interpolative fuzzy inference method, International Journal of General Systems 29 (4), pp. 585-604, (2000). (Scopus) 5. Kelkar, B., Postlethwaite, B.: Enhancing the generality of fuzzy relational models for control, Fuzzy Sets and Systems 100 (1-3), pp. 117-129, (1998). (Scopus) 6. Zhiheng Huang: Rule Model Simplification, Ph.D. dissertation, p. 221, School of Informatics, University of Edinburgh, (2006). 7. Mayuka F. Kwaguchi, Masaaki Miyakoshi: Fuzzy Spline Interpolation in Sparse Fuzzy Rule Bases, pp.95-120, Chapter 6 in: A new paradigm of knowledge engineering by soft computing, Editor: Liya Ding, Fuzzy Logic Systems Institute, World Scientific, ISBN 9810245173, 9789810245177, p.374, (2001). 8. Shimakawa, M.: Calculus of interpolated fuzzy relation type fuzzy reasoning method, International Journal of Innovative Computing, Information and Control 3 (4), August 2007, pp. 839-851, (2007). (Scopus) [90] Kovács, Sz., Kóczy, L.T.: On the membership function of the conclusion generated by linear interpolation in trapezoidal fuzzy rule bases, Pre-proceedings, 4 th International Workshop, Current Issues in Fuzzy Technologies, pp.126-129, Trento, Italy, (1994). [91] Kovács, Sz.: Converting sparse rule base to complete, the sparse-complete rule base transformation, (in Hungarian), MicroCAD 94 International Computer Science Conference, section E, p.9, Miskolc, Hungary, (1994). [92] Cselényi, J., Kovács, Sz., Pap, L.: Simulated fuzzy logic control of an automatic guided vehicle, (in Hungarian), MicroCAD 94 International Computer Science Conference, section J, pp.92-99, Miskolc, Hungary, (1994).
Other research papers [1] Baranyi, P., Yam, Y., Yang, C.T., Kovács, Sz., Várlaki, P., Michelberger P.: SVD Rule Base Complexity Reduction to Arbitrary Inference Operation Based Fuzzy Rule Base, CUHK-MAE-9908, Dept. Mechanical and Automation Eng., Chinese University of Hong Kong, Hong Kong, (1999) [2] Kovács, Sz.: Ph.D. theses (Interpolate Fuzzy Reasoning and its Practical Applications), University of Miskolc, Faculty of Mechanical Engineering, (in Hungarian), (1997). [3] Kovács, Sz.: Application of fuzzy logic control in an AGV path tracking system, Dr.-univ. theses, University of Miskolc, Faculty of Mechanical Engineering, (in Hungarian), (1995). [4] Kóczy, L.T., Kovács, Sz.: On the preservation of convexity and piecewise linearity in linear fuzzy rule interpolation, Technical Report 93-94/402, LIFE Chair of Fuzzy Theory, DSS, Tokyo, Institute of Technology, Japan, p.23, (1993). 1. D. Tikk, P. Baranyi: Comprehensive analysis of a new fuzzy rule interpolation method. IEEE Trans. on Fuzzy Systems, 8(3):281-296, (2000). (Scopus) 2. Tikk, D.: Investigation of fuzzy rule interpolation techniques and the universal approximation property of fuzzy controllers, Ph.D. dissertation, p. 105, Technical University of Budapest, Faculty of Electrical Engineering and Informatics, Department of Telecommunications and Telematics, Budapest, (1999). 3. Zhiheng Huang: Rule Model Simplification, Ph.D. dissertation, p. 221, School of Informatics, University of Edinburgh, (2006). [5] Kovács, Sz.: Fuzzy logic control, M.Sc. theses, Technical University of Budapest, Faculty of Informatics and Electrical Engineering, Budapest, Branch of Computer Science, (in Hungarian), p.116, (1993). [6] Kovács, Sz.: Monitor and development environment for i8088 based microcomputers, M.Sc. theses, Technical University of Budapest, Faculty of Electrical Engineering, Branch of Telecommunication, Budapest, (in Hungarian) (1989). Other papers [1] Kovács, Sz.: A Miskolci Egyetem számítógép-hálózata, Hírlevél, A HUNINET Egyesület lapja, II. évf., 3.szám, pp.5-7, (1994). [2] Kovács, Sz.: Miskolci Egyetem számítógép-hálózata, RICOMNET'94 Regionális Információs
Kommunikációs Hálózatok Konferencia és Kiállítás konferenciakiadvány, nov. 23-25, Miskolc, (in Hungarian), pp.121-128, (1994). [3] Kovács, Sz.: The Campus Computer Network of the University of Miskolc, Proceedings of the Conference on Microeletronic Courses, Miskolci Egyetem, nov., (in Hungarian), p. 5, (1993) [4] Balla László, Kovács Szilveszter, Pivarnyik Attila, Vígh György: Miskolci Egyetem Számítógépes Információs Infrastruktúra Hálózata, Informatika a felsıoktatásban országos konferenciakiadvány, II. szám, szept., Debrecen, (in Hungarian), pp.577-586, (1993). [5] Balla László, Vígh György, Kovács Szilveszter: Miskolci Egyetem Számítógépes Információs Infrastruktúra Hálózata, Információs Infrastruktúra Fejlesztési Program Hírek, 5. szám, dec., (in Hungarian), pp.32-33, (1992). [6] Kovács Szilveszter: A ZX81 bıvítése 16K-ról 17K-ra, Mikroszámítógép Magazin, 4.évf., 9.szám, október, Budapest, (in Hungarian), pp.30-30, (1986).