Gold Price Prediction Method Based on Improved PSO-BP

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Gold Price Prediction Method Based on Improved PSO-BP"

Transcription

1 , pp Gold Prce Predcton Method Based on Improved PSO-BP Yan Wang 1,a,*, Lguo Zhang 2, Yongfu Lu 2 and Jun Guo 1 1 Dept. of computer, North Chna Electrc Power Unversty, Baodng, Hebe, , Chna 2 College of Informaton Scence & Technology, Agrcultural Unversty of Hebe Hebe Baodng, , Chna a Abstract Amed at the hghly nonlnear and uncertanty of gold prce changes, a new method for gold prce predton based on mproved PSO-BP s proposed. By ntroducng mutaton operaton and adaptve adust of nerta weght, the problem of easy to fall nto local optmum, premature, low precson and low later nteraton effcency of PSO are solved. By usng the mproved PSO to optmaze BP neural networ s parameters, the learnng rate and optmzaton capablty of conventonal BP are effectvely mproved. The smulaton results of gold prce predcton show that the predct accuracy of the new method s sgnfcantly hgher than that of conventonal BP neural networ and wavelet neural networ method. And the method s effectve and feasble. Keywords: Partcle swarm optmzaton (PSO), mutaton, adaptve adust, Bacpropagaton neural networ, Gold prce predcton 1. Introducton For a long tme, gold has caught a global attenton for ts functons as a measure of value, means of crculaton, payment nstruments, reserve assets and the world s monetary. It has become a maor proect of the theoretcal and emprcal research that how to effectvely predct the prce of gold. Many scholars, at home and abroad, have made much related research and constructed a number of very valuable theoretcal hypothess and predcton models, such as ARMA model, ARIMA model, adaptve flterng predcton models, varyng coeffcent regresson model, BP neural networ model and so on. Ref [1]has appled wavelet neural networ to predct the gold prce. Zeng lan and Ma Dand establshed the gold prce forcast smulaton model based on BP neural networ optmzed by proecton pursut. Wang Yan used cross valaton and the coeffcent regresson model and multple lnear regresson model to focast gold pce. The man affect factors are U.S. Dollar nde, Ol prces, slver prces, DOW nde, OECD leadng nde, European stoc marets, etc. However, the gold prce fluctuaton trend shows a hgh nonlnearty and uncertanty, whch leads to accurately predct the gold prce s dffcult. Artfcal neural networ predcton method can better handle the nonlnear and uncertan problems, but t also has many shortcomngs, such as: model tranng slow; tme and space complety s hgh; easy to fall nto local optmum. Partcle swarm optmzaton (PSO) s a populaton based stochastc optmzaton technque developed by Dr. Eberhart and Dr. Kennedy n As a group ntellgent search algorthm, t through populaton cooperaton and competton between the partcles to gue group search. And t has many merts, such as parallel global search, the model s smple and convenent, few parameters need to be * Correspondng Author ISSN: IJUNESST Copyrght c 2015 SERSC

2 adusted, convergence s fast and easy mplementaton. Thus, usng PSO algorthm for BP Neural networ pre-search can overcome the defcences of BP algorthm. However, when there are more locally optmums, standard PSO algorthm also easy to fall nto local optmum. Many researchers have made studes for mprovng the PSO algorthm and acheved some success. The paper proposed the gran yeld predcton method based on mproved PSO-BP, and the predcton results show that the predcton model can effectvely mprove the predcton accuracy. 2. BP Neural Networ Artfcal neural networs are powerful tool for predcton of nonlneartes. These mathematcal models comprse ndvual processng unts called neurons that resemble neural actvty. Each processng unts sums weghted nputs and then apples a lnear or nonlnear functon to the resultng sum to determne the output. The neurons are arranged n layers and are combned through ecessve connectvty. Wth herarchcal feed forward networ archtecture, the bacpropagaton networ has receved most attenton. Typcally, three-layer BP neural networ (nput layer, hden layer and output layer) can realze the functon mappngs of n ndependent varables and the m dependent varables. In the study of BP neural networ, the man features are forward transformer of nput sgnal and bac-propagaton of error. Networ s weghts and threshold values are adusted accordng to the predcton error. The sgnal nputted from outse spreads to the output layer and gves the result through processng layer for layer of neurons n nput layer and hden layer. If the epected output can t be obtaned n output layer, t shfts to the conversed spreadng processng and the true value and the error outputted by networ wll return along the coupled access formerly. The error s reduced by modfyng contacted weght value of neurons n every layer and then t shfts to the postve spreadng processng and revolves teraton untl the error s smaller the gven val ue. The topologcal of BP neural networ s shown n Fgure 1. X 1 w w Y 1 X 2 Xn Ym Input layer Hden layer Output layer Fgure 1. The Topologcal of BP Neural Networ Here, X,, X, X are the nput values of neural networ, Y, Y,, Y 1 2 n 2 n 1 are the predctve values, and are networ s weghts. Before usng, the frst tas s to tran the networ. The tranng process ncluded the followng steps. Step 1: Intalze the networ. Accordng to the nput and output of actual system, determne the numbers of nput layer nodes, hden layer nodes and output layer nodes, ntalze, and the threshold value of both hden layer and output layer, and set the learnng rate and the neuron actvaton functon. 254 Copyrght c 2015 SERSC

3 Step 2: Calculate the hden layer output based on formula (1). H n f ( a ) 1,2,, l 1 Where, l s the number of nodes n hden layer, (1) a s the threshold value and f s the actvaton functon of hden layer. In ths paper, we select formula (2) as f. f 1 ) 1 e ( (2) Step 3: Calculate the output value of output layer based on formula (3). O l 1 H b 1,2,, m Where, b s the threshold value of output layer node. (3) Step 4: Calculate the predcton error accordng to the networ predcted output and the desred output. e Y O 1,2,, m (4) Step 5: Update the connecton weghts by the predcton error e. H ( 1 H ) ( ) m 1 e 1,2,, n ; 1,2,, l (5) w H e 1,2,, l ; 1,2,, m (6) Here, s the learnng rate. Step 6: Update the threshold value based on formula (7) and (8). a a H m ( 1 H ) 1 e 1,2,, l (7) b b e 1,2,, m (8) Step 7: Determne whether the teratve ends, and f not, return to Step PSO Algorthm and ts Improvement 3.1. Standard PSO Algorthm Gven n a Q-dmensonal search space, there s a partcle communty composed of n partcles. And the relevant parameters of -th partcle are denoted as follows: the poston vector s denoted by (,,, ), 1, 2,, n. The flyng speed 1 2 Q s denoted by 1 2 v ( v, v,, v ) Q. Up to now, the searched optmal locaton of -th partcle s denoted by p ( p, p,, p ) (Namely P ). the searched optmal 1 2 Q locaton of the whole partcles communty s denoted by p ( p, p,, p ) (Namely G ). To search the optmal soluton n Q- g g 1 g 2 g Q Copyrght c 2015 SERSC 255

4 dmensonal space s to search the partcle n poston. Accordng the three prncples, mantan ts nerta, mantan ts optmal poston and mantan communty optmal poston, the partcle updates ts status durng the moment. In every teraton, the partcles update ther velocty and poston by formula(9). v 1 v c ( P 1 ) c ( G 2 ) v v 1 1 v v v, v 1 1 v v (9) 1 v 1 Here, denotes nerta weght and used to mantan the orgnal rate coeffcents. c and c denote learnng factor and acceleraton coeffcents, 1 2 respectvely. and are the unformly dstrbuted random numbers durng 0 and 1. s constrant factor. [-v,v ] s velocty range for each dmenson of partcle. Standard PSO algorthm flow s shown n Fgure 2. Intalze and v Test ftness of patcles Update v Update X s better than P? P = Yes No X s better than G? Yes G = Meet the convergence? No No 3.2. The Improvement of PSO Yes Output G Fgure 2. Standard PSO Algorthm Flow For the standard PSO algorthm s easy to fall nto local optmum problem, t he paper ntroduced the mutaton operaton to PSO algorthm. The basc ea s to rentalze the partcle after each update wth a certan probablty. The adaptve mutaton operaton method for -th partcle s as follows: r P P (10) random r Here, denotes the -th component of partcle, P denotes mutaton probablty, r the unformly dstrbuted random numbers durng 0 and 1, random 256 Copyrght c 2015 SERSC

5 denotes random number durng ndvual mum and mnmum poston of partcle. Research shows that the lner decreasng nerta wegh can better balance the global search ablty and local search ablty. The paper adopts the followng method to get nerta weght value. 2 ( ) ( ) * ( 2 * / T ( / ) ) (11) start start end T Here, denotes ntal nerta weght ; start end denotes nerta weght of mum teraton number, denotes current teraton number, T denotes mum teraton number The Improved PSO-BP Networ BP neural networ learnng process s the update process of the connecton weghts and thresholds of the networ. The purpose of usng PSO algorthm optmze BP neural networ s to get better networ ntal weghts and thresholds. The basc ea s to use the poston of each ndvual partcle n PSO to represent all of the ntal networ connecton weghts and threshold parameters. Then tae the ndvual ntalzed BP neural networ predcton error as the ndvual s ftness value and through the partcle networ optmzaton to fnd the ntal weghts and thresholds. The detaled algorthm can be summarzed as follows: 1)Desgn and ntalze the networ, normalze the samples. 2)Intalze PSO, such as, populaton sze, partcle structure, locaton and speed. 3)Calculate ftness value of each partcle. The paper taes formula(4) as partcle ftness functon. N ftness y d (12) 1 Here: N denotes tranng sample number, d denotes the desred output of -th sample. y denotes networ computng values of -th sample. 4)Accordng to the ftness value of each partcle, update ts personal poston P and global poston G. 5) Accordng to formula (9), adust the poston and velocty of partcle. 6) Accordng to formula (10), mae adaptve mutaton operaton. 7) If the convergence crtera s met (the number of teraton s reached or the error can accepted), stop teraton. And the G s the ntal parameter values of BP networ, Through further learnng and tranng of BP algorthm can form the predct model. Otherwse, go to step 3 for the net teraton. 4. Gold Prce Predcton based on Improved Accordng to prevous studes and related references, there are many factors affectng Gold prce ncludng Dow Jones nde, Amerca consumer prce nde,usa federal funds rate, Amercan world gold reserves and ol prces, OECD leadng nde and other factors. In the proposed predcton model, tae Dow Jones Copyrght c 2015 SERSC 257

6 nde, Amerca consumer prce nde,amerca dollar nomnal effectve echage rate, world gold reserves, USA federal funds rate and ol prces as nputs and tae Gold prce as the output. Thus the BP neural networ structure s shown n Fgure 3. Then, tae the collected sample data from 1973 to 2000 as tranng sample data and the sample data from 2001 to 2006 as testng sample data. In the test, the relevant parameters of PSO algorthm are as follows: the number of teraton s 50, populaton sze s 20,c1= , c2= and the length of each partcle s 41. Each generaton ndvual ftness curve of mproved PSO algorthm optmzaton process s shown n Fgure 4. The tranng error curves of the the BP networ optmzed by mproved PSO are shown n Fgure 5. The contrast curve of golde prce of forecast results and the real value form 2001 to 2006 years s shown n Fgure 6. The obtaned optmal ntal weghts and thresholds of BP neural networ s shown n Table 1. Predctons contrast of the proposed method and other method for predcted gold prce from 2001 to 2006 s shown n Table 2. Dow Jones Inde Amerca consumer prce nde USA federal funds rate ω ω Ol prce Gold prce Amerca dollar nomnal effectve echage rate World gold reserves Fgure 3. BP Networ Structure for Gold Prce Predcton Fgure 4. Best Indvual Ftness Curve of Improved PSO Fgure 5. Tran Error of Optmzed BP Fgure 6. Cure of Predcted Prce and Real Prce The Intal weghts between nput layer nodes and hden layer nodes The thresholds of hden layer nodes The Intal weghts between output layer nodes and hden layer nodes The thresholds of output layer nodes Table 1. Optmal Intal Weghts and Thresholds Copyrght c 2015 SERSC

7 Year Real Gold Prce BP networ model Predcted prce Table 2. Predcton Contrast Relatve error/(%) Predcted prce Ref Relatve error/(%) Improved PSO-BP networ model Predcted prce Relatve error/(%) As can be seen from Fgure 4, the ndvual ftness obtaned by mproved PSO-BP neural networ method has better optmzaton capablty n evoluton than that of standard BP neural networ. Under the same tranng accuracy and by comparng fgure 5, t can be seen that the proposed method can meet the convergence( ) at 185 th generaton and obvously superor to conventonal BP networ(30588 th generaton) and Ref[method(3690 th generaton). By data comparson of Table 2,the predcton accuracy of mproved PSO-BP method s superor to that of conventonal BP networ and Ref method for the same statstcs data. The mum relatve error of BP networ method,ref[method and mproved PSO-BP method are 4.4%, 2.5% and 0.6, respectvely. The Mean absolute error of the proposed method and Ref method s and From the comparson, t can be seen that the proposed gold prce predcton method s effectve and feasble. 5. Concluson Gold futures prce s the combned result of a large number of factors. Because of hgh nonlnear, hgh nose and because the factors s determne dffcultly, the predcton s comple and dffcult. Tradtonal methods of predctng the prce of gold have emphaszed the ntrnsc value of gold, or dependent on the lnear relatonshp between the prces of gold. The lmtatons are obvous, whch leads to the low predcton precson. The paper proposed the mproved PSO-BP based gold prce predcton method, whch optmzed the BP neural networ parameters through mproved PSO and effectvely mproved the overall learnng ablty and overcome the problem of easy to fall nto local optmum. The test results for gold prce shows the proposed method s sgnfcantly better than BP neural networ method and wavelet neural networ based method, and has good applcaton prospects for gold prce forecast. Acnowledgements Ths wor was supported by the Fundamental Research Funds for the Central Unverstes(2014MS132), Hebe Scence Research and Development Proect of Chna ( ) and Technology Foundaton of Agrcultural Unversty of Hebe (LG ). References [1] K. Y. Zhang, Yu and T. L, Applcaton of wavelet neural networ n predcton of gold prce, Comput. Eng. Applc, vol. 46, pp , (2010). [2] L. Zeng, D. D. Ma and Z. X. Lu, Gold prce forecast based on mproved BP neural networ, Comput. Smul., vol. 27, (2010), pp Copyrght c 2015 SERSC 259

8 [3] Q. Zhang, J. H. Ma and Y. Wang, Study on forecastng of gold prce based on varyng-coeffcent regresson model, Key Engneerng Materals, vol. 456, (2011), pp [4] L. Chen, Gold prce forecastng model based on proecton pursut and neural networ, Comput. Smul, vol. 30, (2013), pp [5] F. Wang, T. Ma and X. Ma, Gold prce forecastng model based on regresson wth support vector machne for partcle swarm optmzaton, J. Lanzhou Unv. Technol., vol. 39, (2013), pp [6] L. P. Xu and M. Z. Luo, Short-term analyss and predcton of gold prce based on ARIMA model, Fnance Econ., vol. 1, (2011), pp [7] X. We, Sensor temperature compensaton technque smulaton based on BP neural networ, Telomna, vol. 11, (2013), pp [8] B. H. M. Sadegh,, A BP-neural networ predctor model for plastc necton moldng process, J. Mater. Process. Technol., vol.103, (2000), pp [9] J. Kennedy and R. Eberhart, Partcle swarm optmzaton. Proceedngs of the Internatonal Conference on Neural Networs, vol. 4, November 27-December 1, 1995, Perth, WA., USA., pp: , (1995). [10] J. H and H. Guo, A modfed partcle swarm optmzaton algorthm, Telomna, vol. 11, (2013), pp [11] X. Q. Yan, Wu and H. Lu, Orthogonal partcle swarm optmzaton algorthm and ts applcaton n crcut desgn, Telomna, vol. 11, (2013), pp [12] C. Y. Zhao, Z. B. Yan and X. G. Lu, Improved adaptve parameter partcle swarm optmzaton algorthm, J. Zheang Unv. (Eng. Sc.), vol. 39, (2011), pp Author Yan Wang, she was born on 12/6/1981. and obtaned the B.Eng. degree and the M.Eng. degree n computer software and theory specalty from School of Control and Computer Engneerng at North Chna Electrc Power Unversty chna at 2004 and 2007 respectvely. Now, she wors as lecturer at School of Control and Computer Engneerng at North Chna Electrc Power Unversty chna. hs research nterests concentrate on the development of software, Computer applcaton and Artfcal ntellgence, etc. 260 Copyrght c 2015 SERSC

Forecasting the Demand of Emergency Supplies: Based on the CBR Theory and BP Neural Network

Forecasting the Demand of Emergency Supplies: Based on the CBR Theory and BP Neural Network 700 Proceedngs of the 8th Internatonal Conference on Innovaton & Management Forecastng the Demand of Emergency Supples: Based on the CBR Theory and BP Neural Network Fu Deqang, Lu Yun, L Changbng School

More information

Forecasting the Direction and Strength of Stock Market Movement

Forecasting the Direction and Strength of Stock Market Movement Forecastng the Drecton and Strength of Stock Market Movement Jngwe Chen Mng Chen Nan Ye cjngwe@stanford.edu mchen5@stanford.edu nanye@stanford.edu Abstract - Stock market s one of the most complcated systems

More information

A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm

A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):1884-1889 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel

More information

Patterns Antennas Arrays Synthesis Based on Adaptive Particle Swarm Optimization and Genetic Algorithms

Patterns Antennas Arrays Synthesis Based on Adaptive Particle Swarm Optimization and Genetic Algorithms IJCSI Internatonal Journal of Computer Scence Issues, Vol. 1, Issue 1, No 2, January 213 ISSN (Prnt): 1694-784 ISSN (Onlne): 1694-814 www.ijcsi.org 21 Patterns Antennas Arrays Synthess Based on Adaptve

More information

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.

More information

Investigation of Modified Bee Colony Algorithm with Particle and Chaos Theory

Investigation of Modified Bee Colony Algorithm with Particle and Chaos Theory Internatonal Journal of Control and Automaton, pp. 311-3 http://dx.do.org/10.1457/jca.015.8..30 Investgaton of Modfed Bee Colony Algorthm wth Partcle and Chaos Theory Guo Cheng Shangluo College, Zhangye,

More information

Lecture 2: Single Layer Perceptrons Kevin Swingler

Lecture 2: Single Layer Perceptrons Kevin Swingler Lecture 2: Sngle Layer Perceptrons Kevn Sngler kms@cs.str.ac.uk Recap: McCulloch-Ptts Neuron Ths vastly smplfed model of real neurons s also knon as a Threshold Logc Unt: W 2 A Y 3 n W n. A set of synapses

More information

Application of an Improved BP Neural Network Model in Enterprise Network Security Forecasting

Application of an Improved BP Neural Network Model in Enterprise Network Security Forecasting 161 A publcaton of VOL. 46, 15 CHEMICAL ENGINEERING TRANSACTIONS Guest Edtors: Peyu Ren, Yancang L, Hupng Song Copyrght 15, AIDIC Servz S.r.l., ISBN 978-88-9568-37-; ISSN 83-916 The Italan Assocaton of

More information

A Binary Quantum-behaved Particle Swarm Optimization Algorithm with Cooperative Approach

A Binary Quantum-behaved Particle Swarm Optimization Algorithm with Cooperative Approach IJCSI Internatonal Journal of Computer Scence Issues, Vol., Issue, No, January 3 ISSN (Prnt): 694-784 ISSN (Onlne): 694-84 www.ijcsi.org A Bnary Quantum-behave Partcle Swarm Optmzaton Algorthm wth Cooperatve

More information

Journal of Economics and Business

Journal of Economics and Business Journal of Economcs and Busness 64 (2012) 275 286 Contents lsts avalable at ScVerse ScenceDrect Journal of Economcs and Busness A multple adaptve wavelet recurrent neural networ model to analyze crude

More information

A heuristic task deployment approach for load balancing

A heuristic task deployment approach for load balancing Xu Gaochao, Dong Yunmeng, Fu Xaodog, Dng Yan, Lu Peng, Zhao Ja Abstract A heurstc task deployment approach for load balancng Gaochao Xu, Yunmeng Dong, Xaodong Fu, Yan Dng, Peng Lu, Ja Zhao * College of

More information

Sciences Shenyang, Shenyang, China.

Sciences Shenyang, Shenyang, China. Advanced Materals Research Vols. 314-316 (2011) pp 1315-1320 (2011) Trans Tech Publcatons, Swtzerland do:10.4028/www.scentfc.net/amr.314-316.1315 Solvng the Two-Obectve Shop Schedulng Problem n MTO Manufacturng

More information

Document Clustering Analysis Based on Hybrid PSO+K-means Algorithm

Document Clustering Analysis Based on Hybrid PSO+K-means Algorithm Document Clusterng Analyss Based on Hybrd PSO+K-means Algorthm Xaohu Cu, Thomas E. Potok Appled Software Engneerng Research Group, Computatonal Scences and Engneerng Dvson, Oak Rdge Natonal Laboratory,

More information

Stock volatility forecasting using Swarm optimized Hybrid Network

Stock volatility forecasting using Swarm optimized Hybrid Network Web Ste: www.jettcs.org Emal: edtor@jettcs.org, edtorjettcs@gmal.com Volume 2, Issue 3, May June 23 ISSN 2278-686 Stock volatlty forecastng usng Swarm optmzed Hybrd Network Puspanjal Mohapatra, Soumya

More information

Optimal Choice of Random Variables in D-ITG Traffic Generating Tool using Evolutionary Algorithms

Optimal Choice of Random Variables in D-ITG Traffic Generating Tool using Evolutionary Algorithms Optmal Choce of Random Varables n D-ITG Traffc Generatng Tool usng Evolutonary Algorthms M. R. Mosav* (C.A.), F. Farab* and S. Karam* Abstract: Impressve development of computer networks has been requred

More information

A Genetic Programming Based Stock Price Predictor together with Mean-Variance Based Sell/Buy Actions

A Genetic Programming Based Stock Price Predictor together with Mean-Variance Based Sell/Buy Actions Proceedngs of the World Congress on Engneerng 28 Vol II WCE 28, July 2-4, 28, London, U.K. A Genetc Programmng Based Stock Prce Predctor together wth Mean-Varance Based Sell/Buy Actons Ramn Rajaboun and

More information

Performance Analysis and Coding Strategy of ECOC SVMs

Performance Analysis and Coding Strategy of ECOC SVMs Internatonal Journal of Grd and Dstrbuted Computng Vol.7, No. (04), pp.67-76 http://dx.do.org/0.457/jgdc.04.7..07 Performance Analyss and Codng Strategy of ECOC SVMs Zhgang Yan, and Yuanxuan Yang, School

More information

MATHEMATICAL ENGINEERING TECHNICAL REPORTS. Sequential Optimizing Investing Strategy with Neural Networks

MATHEMATICAL ENGINEERING TECHNICAL REPORTS. Sequential Optimizing Investing Strategy with Neural Networks MATHEMATICAL ENGINEERING TECHNICAL REPORTS Sequental Optmzng Investng Strategy wth Neural Networks Ryo ADACHI and Akmch TAKEMURA METR 2010 03 February 2010 DEPARTMENT OF MATHEMATICAL INFORMATICS GRADUATE

More information

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..

More information

A New Task Scheduling Algorithm Based on Improved Genetic Algorithm

A New Task Scheduling Algorithm Based on Improved Genetic Algorithm A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng Envronment Congcong Xong, Long Feng, Lxan Chen A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng

More information

The Network flow Motoring System based on Particle Swarm Optimized

The Network flow Motoring System based on Particle Swarm Optimized The Network flow Motorng System based on Partcle Swarm Optmzed Neural Network Adult Educaton College, Hebe Unversty of Archtecture, Zhangjakou Hebe 075000, Chna Abstract The compatblty of the commercal

More information

Hybrid-Learning Methods for Stock Index Modeling

Hybrid-Learning Methods for Stock Index Modeling Hybrd-Learnng Methods for Stock Index Modelng 63 Chapter IV Hybrd-Learnng Methods for Stock Index Modelng Yuehu Chen, Jnan Unversty, Chna Ajth Abraham, Chung-Ang Unversty, Republc of Korea Abstract The

More information

Optimization Model of Reliable Data Storage in Cloud Environment Using Genetic Algorithm

Optimization Model of Reliable Data Storage in Cloud Environment Using Genetic Algorithm Internatonal Journal of Grd Dstrbuton Computng, pp.175-190 http://dx.do.org/10.14257/gdc.2014.7.6.14 Optmzaton odel of Relable Data Storage n Cloud Envronment Usng Genetc Algorthm Feng Lu 1,2,3, Hatao

More information

NEURO-FUZZY INFERENCE SYSTEM FOR E-COMMERCE WEBSITE EVALUATION

NEURO-FUZZY INFERENCE SYSTEM FOR E-COMMERCE WEBSITE EVALUATION NEURO-FUZZY INFERENE SYSTEM FOR E-OMMERE WEBSITE EVALUATION Huan Lu, School of Software, Harbn Unversty of Scence and Technology, Harbn, hna Faculty of Appled Mathematcs and omputer Scence, Belarusan State

More information

Laddered Multilevel DC/AC Inverters used in Solar Panel Energy Systems

Laddered Multilevel DC/AC Inverters used in Solar Panel Energy Systems Proceedngs of the nd Internatonal Conference on Computer Scence and Electroncs Engneerng (ICCSEE 03) Laddered Multlevel DC/AC Inverters used n Solar Panel Energy Systems Fang Ln Luo, Senor Member IEEE

More information

On the Optimal Control of a Cascade of Hydro-Electric Power Stations

On the Optimal Control of a Cascade of Hydro-Electric Power Stations On the Optmal Control of a Cascade of Hydro-Electrc Power Statons M.C.M. Guedes a, A.F. Rbero a, G.V. Smrnov b and S. Vlela c a Department of Mathematcs, School of Scences, Unversty of Porto, Portugal;

More information

The Application of Fractional Brownian Motion in Option Pricing

The Application of Fractional Brownian Motion in Option Pricing Vol. 0, No. (05), pp. 73-8 http://dx.do.org/0.457/jmue.05.0..6 The Applcaton of Fractonal Brownan Moton n Opton Prcng Qng-xn Zhou School of Basc Scence,arbn Unversty of Commerce,arbn zhouqngxn98@6.com

More information

A GENETIC ALGORITHM-BASED METHOD FOR CREATING IMPARTIAL WORK SCHEDULES FOR NURSES

A GENETIC ALGORITHM-BASED METHOD FOR CREATING IMPARTIAL WORK SCHEDULES FOR NURSES 82 Internatonal Journal of Electronc Busness Management, Vol. 0, No. 3, pp. 82-93 (202) A GENETIC ALGORITHM-BASED METHOD FOR CREATING IMPARTIAL WORK SCHEDULES FOR NURSES Feng-Cheng Yang * and We-Tng Wu

More information

"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *

Research Note APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES * Iranan Journal of Scence & Technology, Transacton B, Engneerng, ol. 30, No. B6, 789-794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC

More information

Performance Management and Evaluation Research to University Students

Performance Management and Evaluation Research to University Students 631 A publcaton of CHEMICAL ENGINEERING TRANSACTIONS VOL. 46, 2015 Guest Edtors: Peyu Ren, Yancang L, Hupng Song Copyrght 2015, AIDIC Servz S.r.l., ISBN 978-88-95608-37-2; ISSN 2283-9216 The Italan Assocaton

More information

LSSVM-ABC Algorithm for Stock Price prediction Osman Hegazy 1, Omar S. Soliman 2 and Mustafa Abdul Salam 3

LSSVM-ABC Algorithm for Stock Price prediction Osman Hegazy 1, Omar S. Soliman 2 and Mustafa Abdul Salam 3 LSSVM-ABC Algorthm for Stock Prce predcton Osman Hegazy 1, Omar S. Solman 2 and Mustafa Abdul Salam 3 1, 2 (Faculty of Computers and Informatcs, Caro Unversty, Egypt) 3 (Hgher echnologcal Insttute (H..I),

More information

LITERATURE REVIEW: VARIOUS PRIORITY BASED TASK SCHEDULING ALGORITHMS IN CLOUD COMPUTING

LITERATURE REVIEW: VARIOUS PRIORITY BASED TASK SCHEDULING ALGORITHMS IN CLOUD COMPUTING LITERATURE REVIEW: VARIOUS PRIORITY BASED TASK SCHEDULING ALGORITHMS IN CLOUD COMPUTING 1 MS. POOJA.P.VASANI, 2 MR. NISHANT.S. SANGHANI 1 M.Tech. [Software Systems] Student, Patel College of Scence and

More information

Different Methods of Long-Term Electric Load Demand Forecasting; A Comprehensive Review

Different Methods of Long-Term Electric Load Demand Forecasting; A Comprehensive Review Dfferent Methods of Long-Term Electrc Load Demand Forecastng; A Comprehensve Revew L. Ghods* and M. Kalantar* Abstract: Long-term demand forecastng presents the frst step n plannng and developng future

More information

PAS: A Packet Accounting System to Limit the Effects of DoS & DDoS. Debish Fesehaye & Klara Naherstedt University of Illinois-Urbana Champaign

PAS: A Packet Accounting System to Limit the Effects of DoS & DDoS. Debish Fesehaye & Klara Naherstedt University of Illinois-Urbana Champaign PAS: A Packet Accountng System to Lmt the Effects of DoS & DDoS Debsh Fesehaye & Klara Naherstedt Unversty of Illnos-Urbana Champagn DoS and DDoS DDoS attacks are ncreasng threats to our dgtal world. Exstng

More information

Improved SVM in Cloud Computing Information Mining

Improved SVM in Cloud Computing Information Mining Internatonal Journal of Grd Dstrbuton Computng Vol.8, No.1 (015), pp.33-40 http://dx.do.org/10.1457/jgdc.015.8.1.04 Improved n Cloud Computng Informaton Mnng Lvshuhong (ZhengDe polytechnc college JangSu

More information

Lei Liu, Hua Yang Business School, Hunan University, Changsha, Hunan, P.R. China, 410082. Abstract

Lei Liu, Hua Yang Business School, Hunan University, Changsha, Hunan, P.R. China, 410082. Abstract , pp.377-390 http://dx.do.org/10.14257/jsa.2016.10.4.34 Research on the Enterprse Performance Management Informaton System Development and Robustness Optmzaton based on Data Regresson Analyss and Mathematcal

More information

Mining Feature Importance: Applying Evolutionary Algorithms within a Web-based Educational System

Mining Feature Importance: Applying Evolutionary Algorithms within a Web-based Educational System Mnng Feature Importance: Applyng Evolutonary Algorthms wthn a Web-based Educatonal System Behrouz MINAEI-BIDGOLI 1, and Gerd KORTEMEYER 2, and Wllam F. PUNCH 1 1 Genetc Algorthms Research and Applcatons

More information

IMPACT ANALYSIS OF A CELLULAR PHONE

IMPACT ANALYSIS OF A CELLULAR PHONE 4 th ASA & μeta Internatonal Conference IMPACT AALYSIS OF A CELLULAR PHOE We Lu, 2 Hongy L Bejng FEAonlne Engneerng Co.,Ltd. Bejng, Chna ABSTRACT Drop test smulaton plays an mportant role n nvestgatng

More information

SCHEDULING OF CONSTRUCTION PROJECTS BY MEANS OF EVOLUTIONARY ALGORITHMS

SCHEDULING OF CONSTRUCTION PROJECTS BY MEANS OF EVOLUTIONARY ALGORITHMS SCHEDULING OF CONSTRUCTION PROJECTS BY MEANS OF EVOLUTIONARY ALGORITHMS Magdalena Rogalska 1, Wocech Bożeko 2,Zdzsław Heduck 3, 1 Lubln Unversty of Technology, 2- Lubln, Nadbystrzycka 4., Poland. E-mal:rogalska@akropols.pol.lubln.pl

More information

An Interest-Oriented Network Evolution Mechanism for Online Communities

An Interest-Oriented Network Evolution Mechanism for Online Communities An Interest-Orented Network Evoluton Mechansm for Onlne Communtes Cahong Sun and Xaopng Yang School of Informaton, Renmn Unversty of Chna, Bejng 100872, P.R. Chna {chsun,yang}@ruc.edu.cn Abstract. Onlne

More information

Foreign Exchange Rate Prediction using Computational Intelligence Methods

Foreign Exchange Rate Prediction using Computational Intelligence Methods Internatonal Journal of Computer Informaton Systems and Industral Management Applcatons ISSN 5-7988 Volume 4 () pp 659-67 MIR Labs, wwwmrlabsnet/jcsm/ndehtml Foregn Echange Rate Predcton usng Computatonal

More information

Credit Limit Optimization (CLO) for Credit Cards

Credit Limit Optimization (CLO) for Credit Cards Credt Lmt Optmzaton (CLO) for Credt Cards Vay S. Desa CSCC IX, Ednburgh September 8, 2005 Copyrght 2003, SAS Insttute Inc. All rghts reserved. SAS Propretary Agenda Background Tradtonal approaches to credt

More information

Intelligent Method for Cloud Task Scheduling Based on Particle Swarm Optimization Algorithm

Intelligent Method for Cloud Task Scheduling Based on Particle Swarm Optimization Algorithm Unversty of Nzwa, Oman December 9-11, 2014 Page 39 THE INTERNATIONAL ARAB CONFERENCE ON INFORMATION TECHNOLOGY (ACIT2014) Intellgent Method for Cloud Task Schedulng Based on Partcle Swarm Optmzaton Algorthm

More information

On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features

On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features On-Lne Fault Detecton n Wnd Turbne Transmsson System usng Adaptve Flter and Robust Statstcal Features Ruoyu L Remote Dagnostcs Center SKF USA Inc. 3443 N. Sam Houston Pkwy., Houston TX 77086 Emal: ruoyu.l@skf.com

More information

Forecasting the Prices of TAIEX Options by Using Genetic Programming and Support Vector Regression

Forecasting the Prices of TAIEX Options by Using Genetic Programming and Support Vector Regression Proceedngs of the Internatonal MultConference of Engneers and Computer Scentsts 2015 Vol I, Forecastng the Prces of AIEX Optons by Usng Genetc Programmng and Support Vector Regresson Chh-Mng Hsu, Yng-Ch

More information

ECE544NA Final Project: Robust Machine Learning Hardware via Classifier Ensemble

ECE544NA Final Project: Robust Machine Learning Hardware via Classifier Ensemble 1 ECE544NA Fnal Project: Robust Machne Learnng Hardware va Classfer Ensemble Sa Zhang, szhang12@llnos.edu Dept. of Electr. & Comput. Eng., Unv. of Illnos at Urbana-Champagn, Urbana, IL, USA Abstract In

More information

Robust Design of Public Storage Warehouses. Yeming (Yale) Gong EMLYON Business School

Robust Design of Public Storage Warehouses. Yeming (Yale) Gong EMLYON Business School Robust Desgn of Publc Storage Warehouses Yemng (Yale) Gong EMLYON Busness School Rene de Koster Rotterdam school of management, Erasmus Unversty Abstract We apply robust optmzaton and revenue management

More information

Dynamic Constrained Economic/Emission Dispatch Scheduling Using Neural Network

Dynamic Constrained Economic/Emission Dispatch Scheduling Using Neural Network Dynamc Constraned Economc/Emsson Dspatch Schedulng Usng Neural Network Fard BENHAMIDA 1, Rachd BELHACHEM 1 1 Department of Electrcal Engneerng, IRECOM Laboratory, Unversty of Djllal Labes, 220 00, Sd Bel

More information

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12 14 The Ch-squared dstrbuton PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 1 If a normal varable X, havng mean µ and varance σ, s standardsed, the new varable Z has a mean 0 and varance 1. When ths standardsed

More information

Project Networks With Mixed-Time Constraints

Project Networks With Mixed-Time Constraints Project Networs Wth Mxed-Tme Constrants L Caccetta and B Wattananon Western Australan Centre of Excellence n Industral Optmsaton (WACEIO) Curtn Unversty of Technology GPO Box U1987 Perth Western Australa

More information

THE APPLICATION OF DATA MINING TECHNIQUES AND MULTIPLE CLASSIFIERS TO MARKETING DECISION

THE APPLICATION OF DATA MINING TECHNIQUES AND MULTIPLE CLASSIFIERS TO MARKETING DECISION Internatonal Journal of Electronc Busness Management, Vol. 3, No. 4, pp. 30-30 (2005) 30 THE APPLICATION OF DATA MINING TECHNIQUES AND MULTIPLE CLASSIFIERS TO MARKETING DECISION Yu-Mn Chang *, Yu-Cheh

More information

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting Causal, Explanatory Forecastng Assumes cause-and-effect relatonshp between system nputs and ts output Forecastng wth Regresson Analyss Rchard S. Barr Inputs System Cause + Effect Relatonshp The job of

More information

Descriptive Models. Cluster Analysis. Example. General Applications of Clustering. Examples of Clustering Applications

Descriptive Models. Cluster Analysis. Example. General Applications of Clustering. Examples of Clustering Applications CMSC828G Prncples of Data Mnng Lecture #9 Today s Readng: HMS, chapter 9 Today s Lecture: Descrptve Modelng Clusterng Algorthms Descrptve Models model presents the man features of the data, a global summary

More information

Vision Mouse. Saurabh Sarkar a* University of Cincinnati, Cincinnati, USA ABSTRACT 1. INTRODUCTION

Vision Mouse. Saurabh Sarkar a* University of Cincinnati, Cincinnati, USA ABSTRACT 1. INTRODUCTION Vson Mouse Saurabh Sarkar a* a Unversty of Cncnnat, Cncnnat, USA ABSTRACT The report dscusses a vson based approach towards trackng of eyes and fngers. The report descrbes the process of locatng the possble

More information

Modelling of Web Domain Visits by Radial Basis Function Neural Networks and Support Vector Machine Regression

Modelling of Web Domain Visits by Radial Basis Function Neural Networks and Support Vector Machine Regression Modellng of Web Doman Vsts by Radal Bass Functon Neural Networks and Support Vector Machne Regresson Vladmír Olej, Jana Flpová Insttute of System Engneerng and Informatcs Faculty of Economcs and Admnstraton,

More information

A study on the ability of Support Vector Regression and Neural Networks to Forecast Basic Time Series Patterns

A study on the ability of Support Vector Regression and Neural Networks to Forecast Basic Time Series Patterns A study on the ablty of Support Vector Regresson and Neural Networks to Forecast Basc Tme Seres Patterns Sven F. Crone, Jose Guajardo 2, and Rchard Weber 2 Lancaster Unversty, Department of Management

More information

Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy

Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy 4.02 Quz Solutons Fall 2004 Multple-Choce Questons (30/00 ponts) Please, crcle the correct answer for each of the followng 0 multple-choce questons. For each queston, only one of the answers s correct.

More information

Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic

Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic Lagrange Multplers as Quanttatve Indcators n Economcs Ivan Mezník Insttute of Informatcs, Faculty of Busness and Management, Brno Unversty of TechnologCzech Republc Abstract The quanttatve role of Lagrange

More information

Forecasting and Modelling Electricity Demand Using Anfis Predictor

Forecasting and Modelling Electricity Demand Using Anfis Predictor Journal of Mathematcs and Statstcs 7 (4): 75-8, 0 ISSN 549-3644 0 Scence Publcatons Forecastng and Modellng Electrcty Demand Usng Anfs Predctor M. Mordjaou and B. Boudjema Department of Electrcal Engneerng,

More information

Open Access A Load Balancing Strategy with Bandwidth Constraint in Cloud Computing. Jing Deng 1,*, Ping Guo 2, Qi Li 3, Haizhu Chen 1

Open Access A Load Balancing Strategy with Bandwidth Constraint in Cloud Computing. Jing Deng 1,*, Ping Guo 2, Qi Li 3, Haizhu Chen 1 Send Orders for Reprnts to reprnts@benthamscence.ae The Open Cybernetcs & Systemcs Journal, 2014, 8, 115-121 115 Open Access A Load Balancng Strategy wth Bandwdth Constrant n Cloud Computng Jng Deng 1,*,

More information

Damage detection in composite laminates using coin-tap method

Damage detection in composite laminates using coin-tap method Damage detecton n composte lamnates usng con-tap method S.J. Km Korea Aerospace Research Insttute, 45 Eoeun-Dong, Youseong-Gu, 35-333 Daejeon, Republc of Korea yaeln@kar.re.kr 45 The con-tap test has the

More information

Searching for Interacting Features for Spam Filtering

Searching for Interacting Features for Spam Filtering Searchng for Interactng Features for Spam Flterng Chuanlang Chen 1, Yun-Chao Gong 2, Rongfang Be 1,, and X. Z. Gao 3 1 Department of Computer Scence, Bejng Normal Unversty, Bejng 100875, Chna 2 Software

More information

An Evaluation of the Extended Logistic, Simple Logistic, and Gompertz Models for Forecasting Short Lifecycle Products and Services

An Evaluation of the Extended Logistic, Simple Logistic, and Gompertz Models for Forecasting Short Lifecycle Products and Services An Evaluaton of the Extended Logstc, Smple Logstc, and Gompertz Models for Forecastng Short Lfecycle Products and Servces Charles V. Trappey a,1, Hsn-yng Wu b a Professor (Management Scence), Natonal Chao

More information

A spam filtering model based on immune mechanism

A spam filtering model based on immune mechanism Avalable onlne www.jocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):2533-2540 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A spam flterng model based on mmune mechansm Ya-png

More information

Research Article Integrated Model of Multiple Kernel Learning and Differential Evolution for EUR/USD Trading

Research Article Integrated Model of Multiple Kernel Learning and Differential Evolution for EUR/USD Trading Hndaw Publshng Corporaton e Scentfc World Journal, Artcle ID 914641, 12 pages http://dx.do.org/10.1155/2014/914641 Research Artcle Integrated Model of Multple Kernel Learnng and Dfferental Evoluton for

More information

A Load-Balancing Algorithm for Cluster-based Multi-core Web Servers

A Load-Balancing Algorithm for Cluster-based Multi-core Web Servers Journal of Computatonal Informaton Systems 7: 13 (2011) 4740-4747 Avalable at http://www.jofcs.com A Load-Balancng Algorthm for Cluster-based Mult-core Web Servers Guohua YOU, Yng ZHAO College of Informaton

More information

Logistic Regression. Lecture 4: More classifiers and classes. Logistic regression. Adaboost. Optimization. Multiple class classification

Logistic Regression. Lecture 4: More classifiers and classes. Logistic regression. Adaboost. Optimization. Multiple class classification Lecture 4: More classfers and classes C4B Machne Learnng Hlary 20 A. Zsserman Logstc regresson Loss functons revsted Adaboost Loss functons revsted Optmzaton Multple class classfcaton Logstc Regresson

More information

320 The Internatonal Arab Journal of Informaton Technology, Vol. 5, No. 3, July 2008 Comparsons Between Data Clusterng Algorthms Osama Abu Abbas Computer Scence Department, Yarmouk Unversty, Jordan Abstract:

More information

Optimal Provisioning of Resource in a Cloud Service

Optimal Provisioning of Resource in a Cloud Service ISSN (Onlne): 169-081 95 Optmal Provsonng of Resource n a Cloud Servce Yee Mng Chen 1 Shn-Yng Tsa Department of Industral Engneerng and Management Yuan Ze Unversty 135 Yuan-Tung Rd. Chung-L Tao-Yuan Tawan

More information

What is Candidate Sampling

What is Candidate Sampling What s Canddate Samplng Say we have a multclass or mult label problem where each tranng example ( x, T ) conssts of a context x a small (mult)set of target classes T out of a large unverse L of possble

More information

Imperial College London

Imperial College London F. Fang 1, C.C. Pan 1, I.M. Navon 2, M.D. Pggott 1, G.J. Gorman 1, P.A. Allson 1 and A.J.H. Goddard 1 1 Appled Modellng and Computaton Group Department of Earth Scence and Engneerng Imperal College London,

More information

A Binary Particle Swarm Optimization Algorithm for Lot Sizing Problem

A Binary Particle Swarm Optimization Algorithm for Lot Sizing Problem Journal o Economc and Socal Research 5 (2), -2 A Bnary Partcle Swarm Optmzaton Algorthm or Lot Szng Problem M. Fath Taşgetren & Yun-Cha Lang Abstract. Ths paper presents a bnary partcle swarm optmzaton

More information

Research Article Enhanced Two-Step Method via Relaxed Order of α-satisfactory Degrees for Fuzzy Multiobjective Optimization

Research Article Enhanced Two-Step Method via Relaxed Order of α-satisfactory Degrees for Fuzzy Multiobjective Optimization Hndaw Publshng Corporaton Mathematcal Problems n Engneerng Artcle ID 867836 pages http://dxdoorg/055/204/867836 Research Artcle Enhanced Two-Step Method va Relaxed Order of α-satsfactory Degrees for Fuzzy

More information

Support Vector Machines

Support Vector Machines Support Vector Machnes Max Wellng Department of Computer Scence Unversty of Toronto 10 Kng s College Road Toronto, M5S 3G5 Canada wellng@cs.toronto.edu Abstract Ths s a note to explan support vector machnes.

More information

The Journal of Systems and Software

The Journal of Systems and Software The Journal of Systems and Software 82 (2009) 241 252 Contents lsts avalable at ScenceDrect The Journal of Systems and Software journal homepage: www. elsever. com/ locate/ jss A study of project selecton

More information

Optimized ready mixed concrete truck scheduling for uncertain factors using bee algorithm

Optimized ready mixed concrete truck scheduling for uncertain factors using bee algorithm Songklanakarn J. Sc. Technol. 37 (2), 221-230, Mar.-Apr. 2015 http://www.sst.psu.ac.th Orgnal Artcle Optmzed ready mxed concrete truck schedulng for uncertan factors usng bee algorthm Nuntana Mayteekreangkra

More information

GENETIC ALGORITHM FOR PROJECT SCHEDULING AND RESOURCE ALLOCATION UNDER UNCERTAINTY

GENETIC ALGORITHM FOR PROJECT SCHEDULING AND RESOURCE ALLOCATION UNDER UNCERTAINTY Int. J. Mech. Eng. & Rob. Res. 03 Fady Safwat et al., 03 Research Paper ISS 78 049 www.jmerr.com Vol., o. 3, July 03 03 IJMERR. All Rghts Reserved GEETIC ALGORITHM FOR PROJECT SCHEDULIG AD RESOURCE ALLOCATIO

More information

Maintenance Scheduling by using the Bi-Criterion Algorithm of Preferential Anti-Pheromone

Maintenance Scheduling by using the Bi-Criterion Algorithm of Preferential Anti-Pheromone Leonardo ournal of Scences ISSN 583-0233 Issue 2, anuary-une 2008 p. 43-64 Mantenance Schedulng by usng the B-Crteron Algorthm of Preferental Ant-Pheromone Trantafyllos MYTAKIDIS and Arstds VLACHOS Department

More information

Cluster Analysis. Cluster Analysis

Cluster Analysis. Cluster Analysis Cluster Analyss Cluster Analyss What s Cluster Analyss? Types of Data n Cluster Analyss A Categorzaton of Maor Clusterng Methos Parttonng Methos Herarchcal Methos Densty-Base Methos Gr-Base Methos Moel-Base

More information

Adaptive Fractal Image Coding in the Frequency Domain

Adaptive Fractal Image Coding in the Frequency Domain PROCEEDINGS OF INTERNATIONAL WORKSHOP ON IMAGE PROCESSING: THEORY, METHODOLOGY, SYSTEMS AND APPLICATIONS 2-22 JUNE,1994 BUDAPEST,HUNGARY Adaptve Fractal Image Codng n the Frequency Doman K AI UWE BARTHEL

More information

CONSTRUCTING A SALES FORECASTING MODEL BY INTEGRATING GRA AND ELM:A CASE STUDY FOR RETAIL INDUSTRY

CONSTRUCTING A SALES FORECASTING MODEL BY INTEGRATING GRA AND ELM:A CASE STUDY FOR RETAIL INDUSTRY Internatonal Journal of Electronc Busness Management, Vol. 9, o. 2, pp. 107-121 (2011) 107 COSTRUCTIG A SALES FORECASTIG MODEL BY ITEGRATIG GRA AD ELM:A CASE STUDY FOR RETAIL IDUSTRY Fe-Long Chen and Tsung-Yn

More information

A Novel Adaptive Load Balancing Routing Algorithm in Ad hoc Networks

A Novel Adaptive Load Balancing Routing Algorithm in Ad hoc Networks Journal of Convergence Informaton Technology A Novel Adaptve Load Balancng Routng Algorthm n Ad hoc Networks Zhu Bn, Zeng Xao-png, Xong Xan-sheng, Chen Qan, Fan Wen-yan, We Geng College of Communcaton

More information

A Hybrid Model for Forecasting Sales in Turkish Paint Industry

A Hybrid Model for Forecasting Sales in Turkish Paint Industry Internatonal Journal of Computatonal Intellgence Systems, Vol.2, No. 3 (October, 2009), 277-287 A Hybrd Model for Forecastng Sales n Turksh Pant Industry Alp Ustundag * Department of Industral Engneerng,

More information

Mooring Pattern Optimization using Genetic Algorithms

Mooring Pattern Optimization using Genetic Algorithms 6th World Congresses of Structural and Multdscplnary Optmzaton Ro de Janero, 30 May - 03 June 005, Brazl Moorng Pattern Optmzaton usng Genetc Algorthms Alonso J. Juvnao Carbono, Ivan F. M. Menezes Luz

More information

A COPMARISON OF PARTICLE SWARM OPTIMIZATION AND THE GENETIC ALGORITHM

A COPMARISON OF PARTICLE SWARM OPTIMIZATION AND THE GENETIC ALGORITHM A COPMARISON OF PARTICLE SWARM OPTIMIZATION AND THE GENETIC ALGORITHM Rana Hassan * Babak Cohanm Olver de Weck Massachusetts Insttute of Technology, Cambrdge, MA, 39 Gerhard Venter Vanderplaats Research

More information

Comparison of Weighted Sum Fitness Functions for PSO Optimization of Wideband Medium-gain Antennas

Comparison of Weighted Sum Fitness Functions for PSO Optimization of Wideband Medium-gain Antennas 54 ZHOGKU MA, G. A. E. VAEBOSCH, COMPARISO OF WEIGHTE SUM FITESS FUCTIOS FOR PSO Comparson of Weghted Sum Ftness Functons for PSO Optmzaton of Wdeband Medum-gan Antennas Zhongkun MA, Guy A. E. VAEBOSCH

More information

Global Optimization Algorithms with Application to Non-Life Insurance

Global Optimization Algorithms with Application to Non-Life Insurance Global Optmzaton Algorthms wth Applcaton to Non-Lfe Insurance Problems Ralf Kellner Workng Paper Char for Insurance Economcs Fredrch-Alexander-Unversty of Erlangen-Nürnberg Verson: June 202 GLOBAL OPTIMIZATION

More information

A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION. Michael E. Kuhl Radhamés A. Tolentino-Peña

A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION. Michael E. Kuhl Radhamés A. Tolentino-Peña Proceedngs of the 2008 Wnter Smulaton Conference S. J. Mason, R. R. Hll, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds. A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION

More information

Bayesian Network Based Causal Relationship Identification and Funding Success Prediction in P2P Lending

Bayesian Network Based Causal Relationship Identification and Funding Success Prediction in P2P Lending Proceedngs of 2012 4th Internatonal Conference on Machne Learnng and Computng IPCSIT vol. 25 (2012) (2012) IACSIT Press, Sngapore Bayesan Network Based Causal Relatonshp Identfcaton and Fundng Success

More information

An Efficient Recovery Algorithm for Coverage Hole in WSNs

An Efficient Recovery Algorithm for Coverage Hole in WSNs An Effcent Recover Algorthm for Coverage Hole n WSNs Song Ja 1,*, Wang Balng 1, Peng Xuan 1 School of Informaton an Electrcal Engneerng Harbn Insttute of Technolog at Weha, Shanong, Chna Automatc Test

More information

Blending Roulette Wheel Selection & Rank Selection in Genetic Algorithms

Blending Roulette Wheel Selection & Rank Selection in Genetic Algorithms Internatonal Journal of Machne Learnng and Computng, Vol. 2, o. 4, August 2012 Blendng Roulette Wheel Selecton & Rank Selecton n Genetc Algorthms Rakesh Kumar, Senor Member, IACSIT and Jyotshree, Member,

More information

A Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy S-curve Regression

A Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy S-curve Regression Novel Methodology of Workng Captal Management for Large Publc Constructons by Usng Fuzzy S-curve Regresson Cheng-Wu Chen, Morrs H. L. Wang and Tng-Ya Hseh Department of Cvl Engneerng, Natonal Central Unversty,

More information

Resource Scheduling Scheme Based on Improved Frog Leaping Algorithm in Cloud Environment

Resource Scheduling Scheme Based on Improved Frog Leaping Algorithm in Cloud Environment Informaton technologes Resource Schedulng Scheme Based on Improved Frog Leapng Algorthm n Cloud Envronment Senbo Chen 1, 2 1 School of Computer Scence and Technology, Nanjng Unversty of Aeronautcs and

More information

An Alternative Way to Measure Private Equity Performance

An Alternative Way to Measure Private Equity Performance An Alternatve Way to Measure Prvate Equty Performance Peter Todd Parlux Investment Technology LLC Summary Internal Rate of Return (IRR) s probably the most common way to measure the performance of prvate

More information

Time Delayed Independent Component Analysis for Data Quality Monitoring

Time Delayed Independent Component Analysis for Data Quality Monitoring IWSSIP 1-17th Internatonal Conference on Systems, Sgnals and Image Processng Tme Delayed Independent Component Analyss for Data Qualty Montorng José Márco Faer Sgnal Processng Laboratory, COE/Pol Federal

More information

Calculating the high frequency transmission line parameters of power cables

Calculating the high frequency transmission line parameters of power cables < ' Calculatng the hgh frequency transmsson lne parameters of power cables Authors: Dr. John Dcknson, Laboratory Servces Manager, N 0 RW E B Communcatons Mr. Peter J. Ncholson, Project Assgnment Manager,

More information

An Adaptive and Distributed Clustering Scheme for Wireless Sensor Networks

An Adaptive and Distributed Clustering Scheme for Wireless Sensor Networks 2007 Internatonal Conference on Convergence Informaton Technology An Adaptve and Dstrbuted Clusterng Scheme for Wreless Sensor Networs Xnguo Wang, Xnmng Zhang, Guolang Chen, Shuang Tan Department of Computer

More information

Development of an intelligent system for tool wear monitoring applying neural networks

Development of an intelligent system for tool wear monitoring applying neural networks of Achevements n Materals and Manufacturng Engneerng VOLUME 14 ISSUE 1-2 January-February 2006 Development of an ntellgent system for tool wear montorng applyng neural networks A. Antć a, J. Hodolč a,

More information

Intra-day Trading of the FTSE-100 Futures Contract Using Neural Networks With Wavelet Encodings

Intra-day Trading of the FTSE-100 Futures Contract Using Neural Networks With Wavelet Encodings Submtted to European Journal of Fnance Intra-day Tradng of the FTSE-00 Futures Contract Usng eural etworks Wth Wavelet Encodngs D L Toulson S P Toulson Intellgent Fnancal Systems Lmted Sute 4 Greener House

More information

Optimal Bidding Strategies for Generation Companies in a Day-Ahead Electricity Market with Risk Management Taken into Account

Optimal Bidding Strategies for Generation Companies in a Day-Ahead Electricity Market with Risk Management Taken into Account Amercan J. of Engneerng and Appled Scences (): 8-6, 009 ISSN 94-700 009 Scence Publcatons Optmal Bddng Strateges for Generaton Companes n a Day-Ahead Electrcty Market wth Rsk Management Taken nto Account

More information