Integration of Process Simulation and Data Mining Techniques for the Analysis and Optimization of Process Systems. Balazs Balasko
|
|
- Cory Gordon
- 8 years ago
- Views:
Transcription
1 Theses of the doctoral (PhD) dissertation Integration of Process Simulation and Data Mining Techniques for the Analysis and Optimization of Process Systems Balazs Balasko University of Pannonia PhD School of Chemical and Material Engineering Science Supervisor Janos Abonyi, PhD Sandor Nemeth, PhD Department of Process Engineering Veszprem 2009.
2 1 Introduction and aim of the work Customers satisfaction and the economical challenge of modern technologies claim for a continuous optimization in every field of life. In chemical industry, products with tailored quality values have to be produced while specific costs have to be on a minimal level. Due to its high automation level, chemical industry can provide large amounts of data for these optimization purposes. Unfortunately, as mountains of data gets available, it gets even harder to find approaches to process and analyze such amounts of information, which definitely could have the potential for improvement by getting familiar with the underlying structure of the analyzed system. The problem arises from the phenomena that information sources are distributed along the company and there is no unifying framework whereto all these sources could be integrated. From other point of view, future chemical engineering task are characterized by challenges to continuously improve design, modeling and control techniques, thus improve the efficiency, effectiveness and reliability of all the chemical engineering activities. Non of these can be managed without the exhaustive application of process data, process models and (a priori and extracted) knowledge about the analyzed system. All these tools need to be applied in an integrated way centered around an integrated information environment. From the above statements comes the conclusion that there is always a need for systematic tools that help to integrate information sources and techniques to manage improvement and optimization purposes. Leading chemical companies like DuPont, Dow Chemical or Bayer Technology Services mean that model integrates the organization and as such, their approach leads to the concept of life-cycle modeling. This concept deals with a continuous, vertical and horizontal knowledge and information transfer across the whole company centered around models of different scales, i.e. it is based on hierarchical, multi-scale models where at each level, the appropriate model with the right information content is used. The original aim of my thesis was to develop tools and algorithms for process data analysis of multi-product systems within a research project of Tisza Chemical Group and Cooperative Research Center of Chemical Engineering Institute, but later on it was expanded with a solution approach of the above problem: establish an integrated information environment that collects and 2
3 stores data in a consistent way from heterogeneous sources and whereto developed tools and algorithms can be attached. Regarding these purposes, the thesis provides contributions from the following scientific areas: semi-mechanistic modeling, dynamic simulation, semiqualitative trend analysis, optimal experiment design. Most of presented solutions lie in the cross-section of engineering and informatics while all of them have some bio-inspired elements (neural network model, sequence alignment, evolutionary strategy)- forecasting that in the future, novel methodologies with such exhaustive application of synergies from different fields of science are expected to arise. 2 Experimental tools and methodologies The presented thesis contributes to modeling, simulation, data analysis and experimentation hence during implementation, techniques of the process engineering and data mining communities were applied and improved. The central data warehouse was realized in a MySQL c database, data transfer from the Process History Database module of the analyzed technology was managed by MS Excel. All the models, algorithms were implemented in MATLAB and Simulink software environment with an ODBC data warehouse connection. For particular solutions, MATLAB extensions of the SOM Toolbox, Statistics Toolbox, Data analysis Toolbox and Bioinformatics Toolbox were applied. 3
4 3 Theses 1. A process simulator achieved by integrating historical data based process data warehouse to models of the process and its control system effectively supports analysis and improvement of operating technologies. (Related publications: 6, 8, 12, 17, 19, 21) (a) It has been shown that in the near future of process improvement and optimization only dedicated solutions should exist where information sources are consistent, accessible and the data mining and simulation tools work in an integrated way in order to process effectively all these data, models and knowledge of the system. As center of such an integrated framework, I have established a process data warehouse for a Spheripol c -type technology and connected models of the technology, its control system model and data mining tools via a graphical user interface. (b) To present its effectiveness of such integrated information systems, I have developed a prototype of a process simulator attached to process data warehouse for a multi-product polymer producing plant. The simulator is built in a semi-mechanistic way based on multiscale hierarchical models of technology and its basic and advanced control (APC) system. As the operating APC was originally developed for steady-state operation and there exist frequent dynamic state transitions (product changes), the simulator was structured in order to be able to simulate transition strategies thus testify and qualify them as well. (c) I have successfully applied the above prototype system for estimation of product quality by a new semi-mechanistic product model extension and for extraction of cost-energy relation based on boxplots and quantile-quantile plots. 2. Time series analysis based on symbolic segmentation is well applicable for comparing process data trends. (Related publications: 6, 8, 12, 17, 19, 21) (a) Industrial data acquisition systems collect and store large amount of 4
5 time series of process variables and to follow and to judge these time series is a complicated task even for specialists of the given technology: while comparing two trends, subjective (experience) and objective (distance measure) elements are also needed. I have proposed a semi-qualitative solution where time series are segmented and transformed into symbolic sequences and these are compared by global sequence alignment - a technique in Bio-informatics. Time series are considered to be amino acid sequences and as such this well-known and widely applied technique could be adopted into the field of process engineering. (b) The developed tool has been extended by filtering function in order to be able to process noisy raw data inputs and has been successfully applied to qualify and to group product transitions of the polymer producing technology. A real advantage of my solution is that unlike unsupervised methods (clustering and classification), experimental knowledge of the operators can be explicitly incorporated into the segmentation process hence it supports comparing these trends. 3. Optimal experiment design supported by evolutionary strategy is an effective tool for iterative and interactive model development and parameter identification tasks. (Related publications: 1, 2, 10) Central question of the sequential experiment design method is how to select input profile or time series of a system during the iterative model development phase in order to have the system outputs be most informative regarding the model parameters. This problem can be solved by an iterative-sequential method called optimal experiment design (OED) where the applied extremum-searching algorithm has a key role. The original algorithm was further developed in two elements: (i) I have shown that at these steps, applying evolutionary strategy improves efficiency while (ii) collecting previous results in a database (data warehouse) and using their outcome in the current experiment serves as further improvement for the parameter identification process. In this way, model developments and parameter identification can be managed with less energy efforts and higher reliability. 5
6 4 Publications related to theses Articles in international journals 1. B. Balasko, J.Madar, F. Szeifert, J. Abonyi, Evolutionary Strategy in Iterative Experiment Design, Hungarian Journal of Industrial Chemistry, Special issue on Recent Advantages on Process Engineering, Vol.33. Nr B. Balasko, J. Madar and J. Abonyi, Additive Sequential Evolutionary Design of Experiments, Lecture Notes in Computer Science, Artificial Intelligence and Soft Computing ICAISC Balazs Balasko, Sandor Nemeth, Akos Janecska, Tibor Nagy, Gabor Nagy, Janos Abonyi, Process modeling and simulation for optimization of operating processes, Computer Aided Chemical Engineering, Volume 24, pp , Balazs Balasko, Sandor Nemeth, Gabor Nagy and Janos Abonyi, Integrated Process and Control System Model for Product Quality Control Application to a Polypropylene Plant, Chemical Product and Process Modeling, Vol. 3 Iss. 1, Article 50, B. Balasko and J. Abonyi, What happens to process data in chemical industry: From source to applications - An Overview, Hungarian Journal of Industrial Chemistry, Vol. 35, pp , B. Balasko, J. Abonyi, Symbolic Representation based Qualitative Trend Analysis for Process Transition Qualification and Visualization, Engineering Applications of Artificial Intelligence, 2009, submitted Articles in Hungarian journals 7. Balaskó B., Németh S., Abonyi J., Működő technológia optimalizálása az irányító rendszer modelljének felhasználásával, Acta Agraria Kaposvariensis, Vol. 10. Nr. 3., pp , B. Balaskó, S. Nemeth, J. Abonyi, Time-Series Similarity - Application to Qualitative Process Trend Analysis, Acta Agraria Kaposvariensis,
7 Refereed presentations 9. F.P. Pach, B. Balasko, S. Nemeth, P. Arva, J. Abonyi, Black-Box and First-Principle Model Based Optimization of Operating Technologies, In proc. of 5 th MATHMOD Conference, Vienna, B. Balasko, J. Madar and J. Abonyi, Additive Sequential Evolutionary Design of Experiments, 8 th International Conference on Artificial Intelligence and Soft Computing, Zakopane, Balazs Balasko, Sandor Nemeth and Janos Abonyi, Process Modeling and Simulation for Optimization of Operating Processes, 17 th European Symposium on Computer Aided Process Engineering, Bukarest, B. Balasko, Z. Banko, J. Abonyi, Analyzing Trends by Symbolic Episode Representation and Sequence Alignment, In proc. of 15 th Mediterranean Conference on Automation and Control, Athens, Balazs Balasko, Sandor Nemeth and Janos Abonyi, Application of integrated process and control system model for simulation and improvement of an operating technology, In proc. of 6 th European Congress of Chemical Engineers, Copenhagen, Laszlo Dobos, Balazs Balasko, Sandor Nemeth and Janos Abonyi, Energy and resource saving at operating plants based on the analysis of historical process data, In proceedings of Early-Stage Energy Technologies for Sustainable Future: Assessment Development, Application - EMINENT 2, Veszprém, Balazs Balasko, Sandor Nemeth, Janos Abonyi, Integrated Process and Control System Model for Product Quality Control - a Soft-sensor based Application, In proceedings of European Control Conference, Budapest, 2009, accepted Non-Refereed presentations 16. Abonyi János, Balaskó Balázs, Pach Ferenc Péter, Feil Balázs, Németh Sándor, Árva Péter, Adatbányászat működő technológiák optimálásában, Adatbányászati alkalmazások perspektívái, Veszprém,
8 17. Balaskó B., Németh S., Abonyi J., Epizód alapú adatelemzési technika technológia-üzemeltetési stratégiák elemzésére, 34. Műszaki Kémiai Napok, Veszprém, Balaskó B., Németh S., Abonyi J., Működő technológia optimalizálása az irányító rendszer modelljének felhasználásával, V. Alkalmazott Informatika Konferencia, Kaposvár, B. Balasko, S. Nemeth and J. Abonyi, Qualitative Analysis of Segmeted Time Series by Sequence Alignment, 7th International Conference of Hungarian Researchers on Computational Intelligence, Budapest, B. Balasko, S. Nemeth and J. Abonyi, Hierarchical clustering of product transition strategies based on symbolic trend representation in a multiproduct process, 35. Műszaki Kémiai Napok, Veszprém, B. Balasko, S. Nemeth, J. Abonyi, Time-Series Similarity - Application to Qualitative Process Trend Analysis, VI. Alkalmazott Informatika Konferencia, Kaposvár, 2007 Other 22. Balazs Feil, Balazs Balasko, Janos Abonyi, Visualization of Fuzzy Clusters by Fuzzy Sammon Mapping Projection - Application to the Analysis of Phase Space Trajectories, Soft Computing - A Fusion of Foundations, Methodologies and Applications, Vol. 11 Nr. 5, pp , T. Kenesei, B. Balasko, J. Abonyi, A MATLAB Toolbox and its Webbased Variant for Fuzzy Cluster Analysis, 7th International Conference of Hungarian Researchers on Computational Intelligence, Budapest,
Theses of the doctoral (PhD) dissertation. Pannon University PhD School of Chemical and Material Engineering Science. Supervisor: dr.
Theses of the doctoral (PhD) dissertation PROCESS MODELS AND DATA MINING TECHNIQUES IN DETERMINATION AND CHARACTERIZATION OF SAFE OPERATING REGIMES TAMÁS VARGA Pannon University PhD School of Chemical
More informationSIMULATION AND CONTROL OF BATCH REACTORS
THESES OF THE PhD DISSERTATION SIMULATION AND CONTROL OF BATCH REACTORS dr. Lajos Nagy Supervisor: dr. Ferenc Szeifert CSc, associate professor University of Veszprém Department of Process Engineering
More informationData Mining Techniques for Process Development
Data Mining Techniques for Process Development A dissertation submitted in partial fulfillment of the requirements for the degree of D.Sc. at Hungarian Academy of Sciences János Abonyi Veszprém 21 Preface
More informationCluster Analysis for Data Mining and System Identification
Cluster Analysis for Data Mining and System Identification Bearbeitet von János Abonyi, Balázs Feil 1. Auflage 2007. Buch. xviii, 306 S. Hardcover ISBN 978 3 7643 7987 2 Format (B x L): 21 x 29,7 cm Gewicht:
More informationA MATLAB Toolbox and its Web based Variant for Fuzzy Cluster Analysis
A MATLAB Toolbox and its Web based Variant for Fuzzy Cluster Analysis Tamas Kenesei, Balazs Balasko, and Janos Abonyi University of Pannonia, Department of Process Engineering, P.O. Box 58, H-82 Veszprem,
More informationCOMPUTER AIDED NUMERICAL ANALYSIS OF THE CONTINUOUS GRINDING PROCESSES
COMPUTER AIDED NUMERICAL ANALYSIS OF THE CONTINUOUS GRINDING PROCESSES Theses of PhD Dissertation Written by PIROSKA BUZÁNÉ KIS Information Science PhD School University of Veszprém Supervisors: Zoltán
More informationMonitoring of Complex Industrial Processes based on Self-Organizing Maps and Watershed Transformations
Monitoring of Complex Industrial Processes based on Self-Organizing Maps and Watershed Transformations Christian W. Frey 2012 Monitoring of Complex Industrial Processes based on Self-Organizing Maps and
More informationDeveloping a CRM Platform: a Bulgarian case
Developing a CRM Platform: a Bulgarian case SOFIYA VACHKOVA OmegaSoft Ltd. 51 Aleksandar Malinov Blvd., 1712 Sofia BULGARIA sophy.v@gmail.com http://www.omegasoft.bg ELISSAVETA GOUROVA Faculty of Mathematics
More informationMachine Learning with MATLAB David Willingham Application Engineer
Machine Learning with MATLAB David Willingham Application Engineer 2014 The MathWorks, Inc. 1 Goals Overview of machine learning Machine learning models & techniques available in MATLAB Streamlining the
More informationAn Overview of Knowledge Discovery Database and Data mining Techniques
An Overview of Knowledge Discovery Database and Data mining Techniques Priyadharsini.C 1, Dr. Antony Selvadoss Thanamani 2 M.Phil, Department of Computer Science, NGM College, Pollachi, Coimbatore, Tamilnadu,
More informationComparison of K-means and Backpropagation Data Mining Algorithms
Comparison of K-means and Backpropagation Data Mining Algorithms Nitu Mathuriya, Dr. Ashish Bansal Abstract Data mining has got more and more mature as a field of basic research in computer science and
More informationGraduate Co-op Students Information Manual. Department of Computer Science. Faculty of Science. University of Regina
Graduate Co-op Students Information Manual Department of Computer Science Faculty of Science University of Regina 2014 1 Table of Contents 1. Department Description..3 2. Program Requirements and Procedures
More informationCOMPUTER-AIDED PROCESS MODELLING
COMPUTER-AIDED PROCESS MODELLING Theses of Ph.D. dissertation written by ROZÁLIA PIGLER LAKNER Supervisor: Professor Katalin Hangos Information Science Ph.D. School Department of Computer Science University
More informationPhD Theses STUDY OF THE SOLVENT GRADIENT SIMULATED MOVING BED PREPARATIVE LIQUID CHROMATOGRAPHIC PROCESS. Written by Melinda Nagy
PhD Theses STUDY OF THE SOLVENT GRADIENT SIMULATED MOVING BED PREPARATIVE LIQUID CHROMATOGRAPHIC PROCESS Written by Melinda Nagy Consultants Tibor Szánya Géza Horváth University of Pannonia Department
More informationPRACTICAL DATA MINING IN A LARGE UTILITY COMPANY
QÜESTIIÓ, vol. 25, 3, p. 509-520, 2001 PRACTICAL DATA MINING IN A LARGE UTILITY COMPANY GEORGES HÉBRAIL We present in this paper the main applications of data mining techniques at Electricité de France,
More informationThe Masters of Science in Information Systems & Technology
The Masters of Science in Information Systems & Technology College of Engineering and Computer Science University of Michigan-Dearborn A Rackham School of Graduate Studies Program PH: 313-593-5361; FAX:
More informationDoctor of Philosophy in Computer Science
Doctor of Philosophy in Computer Science Background/Rationale The program aims to develop computer scientists who are armed with methods, tools and techniques from both theoretical and systems aspects
More informationCourse 803401 DSS. Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization
Oman College of Management and Technology Course 803401 DSS Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization CS/MIS Department Information Sharing
More informationnot possible or was possible at a high cost for collecting the data.
Data Mining and Knowledge Discovery Generating knowledge from data Knowledge Discovery Data Mining White Paper Organizations collect a vast amount of data in the process of carrying out their day-to-day
More informationHow To Use Neural Networks In Data Mining
International Journal of Electronics and Computer Science Engineering 1449 Available Online at www.ijecse.org ISSN- 2277-1956 Neural Networks in Data Mining Priyanka Gaur Department of Information and
More informationINVESTIGATION OF COLOUR MEMORY
INVESTIGATION OF COLOUR MEMORY PH.D. THESES Tünde Tarczali Supervisor: Dr. Peter Bodrogi Doctoral School of Information Sciences University of Pannonia 2007 Introduction Colour memory plays an important
More informationQuality Management Tools Of Chemical And Bio Industrial Data Systems And Procedures. Gergely Viczián
Ph.D. Thesis Quality Management Tools Of Chemical And Bio Industrial Data Systems And Procedures Gergely Viczián M. Sc. in Electrical engineering and Economy Ph.D. advisor: Dr. Klara Kollár-Hunek Consulant:
More informationFRANCESCO BELLOCCHIO S CURRICULUM VITAE ET STUDIORUM
FRANCESCO BELLOCCHIO S CURRICULUM VITAE ET STUDIORUM April 2011 Index Personal details and education 1 Research activities 2 Teaching and tutorial activities 3 Conference organization and review activities
More informationData Mining Solutions for the Business Environment
Database Systems Journal vol. IV, no. 4/2013 21 Data Mining Solutions for the Business Environment Ruxandra PETRE University of Economic Studies, Bucharest, Romania ruxandra_stefania.petre@yahoo.com Over
More informationApplication of Data Mining Methods in Health Care Databases
6 th International Conference on Applied Informatics Eger, Hungary, January 27 31, 2004. Application of Data Mining Methods in Health Care Databases Ágnes Vathy-Fogarassy Department of Mathematics and
More informationOPC COMMUNICATION IN REAL TIME
OPC COMMUNICATION IN REAL TIME M. Mrosko, L. Mrafko Slovak University of Technology, Faculty of Electrical Engineering and Information Technology Ilkovičova 3, 812 19 Bratislava, Slovak Republic Abstract
More informationChapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization
Turban, Aronson, and Liang Decision Support Systems and Intelligent Systems, Seventh Edition Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization
More informationAbout the NeuroFuzzy Module of the FuzzyTECH5.5 Software
About the NeuroFuzzy Module of the FuzzyTECH5.5 Software Ágnes B. Simon, Dániel Biró College of Nyíregyháza, Sóstói út 31, simona@nyf.hu, bibby@freemail.hu Abstract: Our online edition of the software
More informationData Mining and Neural Networks in Stata
Data Mining and Neural Networks in Stata 2 nd Italian Stata Users Group Meeting Milano, 10 October 2005 Mario Lucchini e Maurizo Pisati Università di Milano-Bicocca mario.lucchini@unimib.it maurizio.pisati@unimib.it
More informationGYAN VIHAR SCHOOL OF ENGINEERING & TECHNOLOGY M. TECH. CSE (2 YEARS PROGRAM)
GYAN VIHAR SCHOOL OF ENGINEERING & TECHNOLOGY M. TECH. CSE (2 YEARS PROGRAM) Need, objectives and main features of the Match. (CSE) Curriculum The main objective of the program is to develop manpower for
More informationData Mining Analysis of a Complex Multistage Polymer Process
Data Mining Analysis of a Complex Multistage Polymer Process Rolf Burghaus, Daniel Leineweber, Jörg Lippert 1 Problem Statement Especially in the highly competitive commodities market, the chemical process
More informationInternational Journal of Computer Science Trends and Technology (IJCST) Volume 2 Issue 3, May-Jun 2014
RESEARCH ARTICLE OPEN ACCESS A Survey of Data Mining: Concepts with Applications and its Future Scope Dr. Zubair Khan 1, Ashish Kumar 2, Sunny Kumar 3 M.Tech Research Scholar 2. Department of Computer
More informationHealthcare Measurement Analysis Using Data mining Techniques
www.ijecs.in International Journal Of Engineering And Computer Science ISSN:2319-7242 Volume 03 Issue 07 July, 2014 Page No. 7058-7064 Healthcare Measurement Analysis Using Data mining Techniques 1 Dr.A.Shaik
More informationIs a Data Scientist the New Quant? Stuart Kozola MathWorks
Is a Data Scientist the New Quant? Stuart Kozola MathWorks 2015 The MathWorks, Inc. 1 Facts or information used usually to calculate, analyze, or plan something Information that is produced or stored by
More informationDynamic Data in terms of Data Mining Streams
International Journal of Computer Science and Software Engineering Volume 2, Number 1 (2015), pp. 1-6 International Research Publication House http://www.irphouse.com Dynamic Data in terms of Data Mining
More informationCourse Syllabus For Operations Management. Management Information Systems
For Operations Management and Management Information Systems Department School Year First Year First Year First Year Second year Second year Second year Third year Third year Third year Third year Third
More informationFluency With Information Technology CSE100/IMT100
Fluency With Information Technology CSE100/IMT100 ),7 Larry Snyder & Mel Oyler, Instructors Ariel Kemp, Isaac Kunen, Gerome Miklau & Sean Squires, Teaching Assistants University of Washington, Autumn 1999
More informationHow To Get A Computer Engineering Degree
COMPUTER ENGINEERING GRADUTE PROGRAM FOR MASTER S DEGREE (With Thesis) PREPARATORY PROGRAM* COME 27 Advanced Object Oriented Programming 5 COME 21 Data Structures and Algorithms COME 22 COME 1 COME 1 COME
More informationUse of a distributed simulation environment for training in Supply Chain decision making
Ian David Lockhart Bogle and Michael Fairweather (Editors), Proceedings of the 22nd European Symposium on Computer Aided Process Engineering, 17-20 June 2012, London. 2012 Elsevier B.V. All rights reserved
More informationVisualization methods for patent data
Visualization methods for patent data Treparel 2013 Dr. Anton Heijs (CTO & Founder) Delft, The Netherlands Introduction Treparel can provide advanced visualizations for patent data. This document describes
More informationVisualization of large data sets using MDS combined with LVQ.
Visualization of large data sets using MDS combined with LVQ. Antoine Naud and Włodzisław Duch Department of Informatics, Nicholas Copernicus University, Grudziądzka 5, 87-100 Toruń, Poland. www.phys.uni.torun.pl/kmk
More informationArtificial Intelligence and Robotics @ Politecnico di Milano. Presented by Matteo Matteucci
1 Artificial Intelligence and Robotics @ Politecnico di Milano Presented by Matteo Matteucci What is Artificial Intelligence «The field of theory & development of computer systems able to perform tasks
More informationBusiness Intelligence and Decision Support Systems
Chapter 12 Business Intelligence and Decision Support Systems Information Technology For Management 7 th Edition Turban & Volonino Based on lecture slides by L. Beaubien, Providence College John Wiley
More informationDS6 Phase 4 Napoli group Astroneural 1,0 is available and includes tools for supervised and unsupervised data mining:
DS6 Phase 4 Napoli group Astroneural 1,0 is available and includes tools for supervised and unsupervised data mining: Preprocessing & visualization Supervised (MLP, RBF) Unsupervised (PPS, NEC+dendrogram,
More informationSanjeev Kumar. contribute
RESEARCH ISSUES IN DATAA MINING Sanjeev Kumar I.A.S.R.I., Library Avenue, Pusa, New Delhi-110012 sanjeevk@iasri.res.in 1. Introduction The field of data mining and knowledgee discovery is emerging as a
More informationMobile Phone APP Software Browsing Behavior using Clustering Analysis
Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management Bali, Indonesia, January 7 9, 2014 Mobile Phone APP Software Browsing Behavior using Clustering Analysis
More informationQuality Assessment in Spatial Clustering of Data Mining
Quality Assessment in Spatial Clustering of Data Mining Azimi, A. and M.R. Delavar Centre of Excellence in Geomatics Engineering and Disaster Management, Dept. of Surveying and Geomatics Engineering, Engineering
More informationIndustry and education in electrical engineering
Industry and education in electrical engineering LABORATORIES, CURRICULUM AND DOCTORAL POSSIBILITIES SZILVIA NAGY 3RD FEBRUARY, 2015. Location of the Széchenyi University 2 Location of the Széchenyi University
More informationBASIC STATISTICAL METHODS FOR GENOMIC DATA ANALYSIS
BASIC STATISTICAL METHODS FOR GENOMIC DATA ANALYSIS SEEMA JAGGI Indian Agricultural Statistics Research Institute Library Avenue, New Delhi-110 012 seema@iasri.res.in Genomics A genome is an organism s
More informationDEPARTMENT OF PETROLEUM ENGINEERING Graduate Program (Version 2002)
DEPARTMENT OF PETROLEUM ENGINEERING Graduate Program (Version 2002) COURSE DESCRIPTION PETE 512 Advanced Drilling Engineering I (3-0-3) This course provides the student with a thorough understanding of
More informationBig Data Analytics. Tools and Techniques
Big Data Analytics Basic concepts of analyzing very large amounts of data Dr. Ing. Morris Riedel Adjunct Associated Professor School of Engineering and Natural Sciences, University of Iceland Research
More informationEnhanced Boosted Trees Technique for Customer Churn Prediction Model
IOSR Journal of Engineering (IOSRJEN) ISSN (e): 2250-3021, ISSN (p): 2278-8719 Vol. 04, Issue 03 (March. 2014), V5 PP 41-45 www.iosrjen.org Enhanced Boosted Trees Technique for Customer Churn Prediction
More informationComputer Information Systems
Computer Information System Courses Description 0309331 0306331 0309332 0306332 0309334 0306334 0309341 0306341 0309353 0306353 Database Systems Introduction to database systems, entity-relationship data
More informationDoctor of Philosophy in Informatics
Doctor of Philosophy in Informatics 2014 Handbook Indiana University established the School of Informatics and Computing as a place where innovative multidisciplinary programs could thrive, a program where
More informationBIG DATA IN THE CLOUD : CHALLENGES AND OPPORTUNITIES MARY- JANE SULE & PROF. MAOZHEN LI BRUNEL UNIVERSITY, LONDON
BIG DATA IN THE CLOUD : CHALLENGES AND OPPORTUNITIES MARY- JANE SULE & PROF. MAOZHEN LI BRUNEL UNIVERSITY, LONDON Overview * Introduction * Multiple faces of Big Data * Challenges of Big Data * Cloud Computing
More informationStandardization of Components, Products and Processes with Data Mining
B. Agard and A. Kusiak, Standardization of Components, Products and Processes with Data Mining, International Conference on Production Research Americas 2004, Santiago, Chile, August 1-4, 2004. Standardization
More informationBig Data: Rethinking Text Visualization
Big Data: Rethinking Text Visualization Dr. Anton Heijs anton.heijs@treparel.com Treparel April 8, 2013 Abstract In this white paper we discuss text visualization approaches and how these are important
More informationPatent Big Data Analysis by R Data Language for Technology Management
, pp. 69-78 http://dx.doi.org/10.14257/ijseia.2016.10.1.08 Patent Big Data Analysis by R Data Language for Technology Management Sunghae Jun * Department of Statistics, Cheongju University, 360-764, Korea
More informationMeta-learning. Synonyms. Definition. Characteristics
Meta-learning Włodzisław Duch, Department of Informatics, Nicolaus Copernicus University, Poland, School of Computer Engineering, Nanyang Technological University, Singapore wduch@is.umk.pl (or search
More informationFinal Year Projects at itm. Topics 2010/2011
Final Year Projects at itm Topics 2010/2011 Chair of Information Technology in Mechanical Engineering Prof. Dr.-Ing. B. Vogel-Heuser Prof. Dr.-Ing. Frank Schiller Prof. Dr.-Ing. Klaus Bender Technische
More informationModeling and Design of Intelligent Agent System
International Journal of Control, Automation, and Systems Vol. 1, No. 2, June 2003 257 Modeling and Design of Intelligent Agent System Dae Su Kim, Chang Suk Kim, and Kee Wook Rim Abstract: In this study,
More informationA Contribution to Expert Decision-based Virtual Product Development
A Contribution to Expert Decision-based Virtual Product Development László Horváth, Imre J. Rudas Institute of Intelligent Engineering Systems, John von Neumann Faculty of Informatics, Óbuda University,
More informationCURRICULUM VITAE PETROS KARVELIS
CURRICULUM VITAE PETROS KARVELIS PERSONAL INFORMATION First Last Name Address E-Mail Petros Karvelis D. Kotrotsou 10B, Stavraki, Ioannina, Greece pkarvelis@gmail.com EDUCATION BSc in Computer Science,
More informationE-Learning Using Data Mining. Shimaa Abd Elkader Abd Elaal
E-Learning Using Data Mining Shimaa Abd Elkader Abd Elaal -10- E-learning using data mining Shimaa Abd Elkader Abd Elaal Abstract Educational Data Mining (EDM) is the process of converting raw data from
More informationA Spatial Decision Support System for Property Valuation
A Spatial Decision Support System for Property Valuation Katerina Christopoulou, Muki Haklay Department of Geomatic Engineering, University College London, Gower Street, London WC1E 6BT Tel. +44 (0)20
More informationFUZZY CLUSTERING ANALYSIS OF DATA MINING: APPLICATION TO AN ACCIDENT MINING SYSTEM
International Journal of Innovative Computing, Information and Control ICIC International c 0 ISSN 34-48 Volume 8, Number 8, August 0 pp. 4 FUZZY CLUSTERING ANALYSIS OF DATA MINING: APPLICATION TO AN ACCIDENT
More informationIntroduction to MATLAB Gergely Somlay Application Engineer gergely.somlay@gamax.hu
Introduction to MATLAB Gergely Somlay Application Engineer gergely.somlay@gamax.hu 2012 The MathWorks, Inc. 1 What is MATLAB? High-level language Interactive development environment Used for: Numerical
More informationGraduate School of Informatics
Graduate School of Informatics Admissions Policy '( ) ' ' - Master's Degree Program Major Enrollment Capacity 40 40 Doctor's Degree Program Major Enrollment Capacity 8 1 M. Entrance examination for international
More informationDATA MINING TECHNOLOGY. Keywords: data mining, data warehouse, knowledge discovery, OLAP, OLAM.
DATA MINING TECHNOLOGY Georgiana Marin 1 Abstract In terms of data processing, classical statistical models are restrictive; it requires hypotheses, the knowledge and experience of specialists, equations,
More informationChapter 5. Warehousing, Data Acquisition, Data. Visualization
Decision Support Systems and Intelligent Systems, Seventh Edition Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization 5-1 Learning Objectives
More informationCOURSE CATALOGUE 2013-2014
COURSE CATALOGUE 201-201 Field: COMPUTER SCIENCE Programme: Bachelor s Degree Programme in Computer Science (Informatics) Length of studies: years (6 semesters) Number of ECTS Credits: 180 +0 for the B.Sc.
More informationHow To Use Data Mining For Knowledge Management In Technology Enhanced Learning
Proceedings of the 6th WSEAS International Conference on Applications of Electrical Engineering, Istanbul, Turkey, May 27-29, 2007 115 Data Mining for Knowledge Management in Technology Enhanced Learning
More informationPreprocessing, Management, and Analysis of Mass Spectrometry Proteomics Data
Preprocessing, Management, and Analysis of Mass Spectrometry Proteomics Data M. Cannataro, P. H. Guzzi, T. Mazza, and P. Veltri Università Magna Græcia di Catanzaro, Italy 1 Introduction Mass Spectrometry
More informationAn Automatic Optical Inspection System for the Diagnosis of Printed Circuits Based on Neural Networks
An Automatic Optical Inspection System for the Diagnosis of Printed Circuits Based on Neural Networks Ahmed Nabil Belbachir 1, Alessandra Fanni 2, Mario Lera 3 and Augusto Montisci 2 1 Vienna University
More informationCredit Card Fraud Detection Using Self Organised Map
International Journal of Information & Computation Technology. ISSN 0974-2239 Volume 4, Number 13 (2014), pp. 1343-1348 International Research Publications House http://www. irphouse.com Credit Card Fraud
More informationMachine Learning and Data Analysis overview. Department of Cybernetics, Czech Technical University in Prague. http://ida.felk.cvut.
Machine Learning and Data Analysis overview Jiří Kléma Department of Cybernetics, Czech Technical University in Prague http://ida.felk.cvut.cz psyllabus Lecture Lecturer Content 1. J. Kléma Introduction,
More informationUsing reporting and data mining techniques to improve knowledge of subscribers; applications to customer profiling and fraud management
Using reporting and data mining techniques to improve knowledge of subscribers; applications to customer profiling and fraud management Paper Jean-Louis Amat Abstract One of the main issues of operators
More informationAN EXCHANGE LANGUAGE FOR PROCESS MODELLING AND MODEL MANAGEMENT
AN EXCHANGE LANGUAGE FOR PROCESS MODELLING AND MODEL MANAGEMENT Huaizhong Li C. Peng Lam School of Computer and Information Science Edith Cowan University, Perth, WA 6050, Australia email: {h.li,c.lam@ecu.edu.au}
More informationLluis Belanche + Alfredo Vellido. Intelligent Data Analysis and Data Mining
Lluis Belanche + Alfredo Vellido Intelligent Data Analysis and Data Mining a.k.a. Data Mining II Office 319, Omega, BCN EET, office 107, TR 2, Terrassa avellido@lsi.upc.edu skype, gtalk: avellido Tels.:
More informationUsing Data Mining for Mobile Communication Clustering and Characterization
Using Data Mining for Mobile Communication Clustering and Characterization A. Bascacov *, C. Cernazanu ** and M. Marcu ** * Lasting Software, Timisoara, Romania ** Politehnica University of Timisoara/Computer
More informationSummary: Natalia Futekova * Vladimir Monov **
in Small and Medium-Sized Enterprises Natalia Futekova * Vladimir Monov ** Summary: The paper is concerned with problems arising in the implementation process of ERP systems including the risks of severe
More informationARTIFICIAL INTELLIGENCE METHODS IN EARLY MANUFACTURING TIME ESTIMATION
1 ARTIFICIAL INTELLIGENCE METHODS IN EARLY MANUFACTURING TIME ESTIMATION B. Mikó PhD, Z-Form Tool Manufacturing and Application Ltd H-1082. Budapest, Asztalos S. u 4. Tel: (1) 477 1016, e-mail: miko@manuf.bme.hu
More informationPhD in Computer Sciences
SUKKUR INSTITUTE OF BUSINESS ADMINISTRATION Merit-Quality-Excellence Schema of Studies for PhD in Computer Sciences (2013-2014) DEPARTMENT OF COMPUTER SCIENCE FACULTY OF SCIENCE AND INFORMATION TECHNOLOGY
More informationVisualisation of CRM Reports and Indicators in the Electric Power Supply Enterprise
Jelica Trninić Imre Petkovič Visualisation of CRM Reports and Indicators in the Electric Power Supply Enterprise Article Info:, Vol. 4 (2009), No. 2, pp. 035-039 Received 12 Jun 2009 Accepted 24 August
More informationMasters in Information Technology
Computer - Information Technology MSc & MPhil - 2015/6 - July 2015 Masters in Information Technology Programme Requirements Taught Element, and PG Diploma in Information Technology: 120 credits: IS5101
More informationA Systemic Artificial Intelligence (AI) Approach to Difficult Text Analytics Tasks
A Systemic Artificial Intelligence (AI) Approach to Difficult Text Analytics Tasks Text Analytics World, Boston, 2013 Lars Hard, CTO Agenda Difficult text analytics tasks Feature extraction Bio-inspired
More informationAbdullah Mohammed Abdullah Khamis
Abdullah Mohammed Abdullah Khamis Jeddah, Saudi Arabia Email: Abdullahkhamis@gmail.com Mobile: +966 567243182 Tel: +966 2 6340699 (Yemeni) Research and Professional Objective To Complete my Ph.D. in Pattern
More informationClassification of Engineering Consultancy Firms Using Self-Organizing Maps: A Scientific Approach
International Journal of Civil & Environmental Engineering IJCEE-IJENS Vol:13 No:03 46 Classification of Engineering Consultancy Firms Using Self-Organizing Maps: A Scientific Approach Mansour N. Jadid
More informationEM Clustering Approach for Multi-Dimensional Analysis of Big Data Set
EM Clustering Approach for Multi-Dimensional Analysis of Big Data Set Amhmed A. Bhih School of Electrical and Electronic Engineering Princy Johnson School of Electrical and Electronic Engineering Martin
More informationUsing Expert System in the Military Technology Research and Development
MIKLÓS ZRÍNYI NATIONAL DEFENSE UNIVERSITY Doctoral Committee MAJOR GÁBOR HANGYA Using Expert System in the Military Technology Research and Development author s review and official critiques of the entitled
More informationASSOCIATION RULE MINING ON WEB LOGS FOR EXTRACTING INTERESTING PATTERNS THROUGH WEKA TOOL
International Journal Of Advanced Technology In Engineering And Science Www.Ijates.Com Volume No 03, Special Issue No. 01, February 2015 ISSN (Online): 2348 7550 ASSOCIATION RULE MINING ON WEB LOGS FOR
More informationDEGREE CURRICULUM BIG DATA ANALYTICS SPECIALITY. MASTER in Informatics Engineering
DEGREE CURRICULUM BIG DATA ANALYTICS SPECIALITY MASTER in Informatics Engineering Module general information Module name BIG DATA ANALYTICS SPECIALITY Typology Optional ECTS 18 Temporal organization C1S2
More informationA Case Retrieval Method for Knowledge-Based Software Process Tailoring Using Structural Similarity
A Case Retrieval Method for Knowledge-Based Software Process Tailoring Using Structural Similarity Dongwon Kang 1, In-Gwon Song 1, Seunghun Park 1, Doo-Hwan Bae 1, Hoon-Kyu Kim 2, and Nobok Lee 2 1 Department
More informationTowards a Big Data Taxonomy. Bill Mandrick, PhD Data Tactics Version 26_August_2013
Towards a Big Data Taxonomy Bill Mandrick, PhD Data Tactics Version 26_August_2013 Scientific Taxonomies Represent Types of Processes Types of Objects Physical Objects Information Artifacts Types of Characteristics
More informationMEng, BSc Applied Computer Science
School of Computing FACULTY OF ENGINEERING MEng, BSc Applied Computer Science Year 1 COMP1212 Computer Processor Effective programming depends on understanding not only how to give a machine instructions
More informationBOOSTING - A METHOD FOR IMPROVING THE ACCURACY OF PREDICTIVE MODEL
The Fifth International Conference on e-learning (elearning-2014), 22-23 September 2014, Belgrade, Serbia BOOSTING - A METHOD FOR IMPROVING THE ACCURACY OF PREDICTIVE MODEL SNJEŽANA MILINKOVIĆ University
More informationSearch and Data Mining: Techniques. Applications Anya Yarygina Boris Novikov
Search and Data Mining: Techniques Applications Anya Yarygina Boris Novikov Introduction Data mining applications Data mining system products and research prototypes Additional themes on data mining Social
More informationKnowledge Discovery from Data Bases Proposal for a MAP-I UC
Knowledge Discovery from Data Bases Proposal for a MAP-I UC P. Brazdil 1, João Gama 1, P. Azevedo 2 1 Universidade do Porto; 2 Universidade do Minho; 1 Knowledge Discovery from Data Bases We are deluged
More informationUniGR Workshop: Big Data «The challenge of visualizing big data»
Dept. ISC Informatics, Systems & Collaboration UniGR Workshop: Big Data «The challenge of visualizing big data» Dr Ir Benoît Otjacques Deputy Scientific Director ISC The Future is Data-based Can we help?
More informationMaster of Business Systems
Aim This Masters-Programme is primarily designed to develop participants who wish to take greater control over, and make a more direct contribution to change in their organisations via the development
More information