Hybrid Evolution of Heterogeneous Neural Networks

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Hybrid Evolution of Heterogeneous Neural Networks"

Transcription

1 Hybrid Evolution of Heterogeneous Neural Networks Zdeněk Buk Miroslav Šnorek Computational Intelligence Group Department of Computer Science and Engineering Faculty of Electrical Engineering Czech Technical University in Prague ICANN 2008

2 Outline Continual Evolution Algorithm (CEA) description Data structures encoding of the individuals Evolution process Control functions Testing, experiments Population behavior Conclusion

3 Continual Evolution Algorithm Hybrid genetic algorithm combination of genetic and gradient-based methods Separate evolution of structure and parameters of individuals (models, neural networks) Variable population size Sequential replacement of individuals evolution in continual time dimension age parameter of each individual

4 Individuals encoding x i = a i, p i, s i, b i Separate evolution of structure and parameters of individuals (models, neural networks)

5 Individuals encoding x i = a i, p i, s i, b i age of the individual

6 Individuals encoding x i = a i, p i, s i, b i structural vector

7 Individuals encoding x i = a i, p i, s i, b i structural vector topology of the network

8 Individuals encoding x i = a i, p i, s i, b i structural vector topology of the network activation functions

9 Individuals encoding x i = a i, p i, s i, b i parametric vector behavioral vector

10 Individuals encoding x i = a i, p i, s i, b i parametric vector behavioral vector weights

11 Individuals encoding x i = a i, p i, s i, b i

12 Evolution process Hybrid genetic algorithm combination of genetic and gradient-based methods 2 Dimensional evolution

13 Evolution process

14 Crossover and mutation Individual 1 p 1 s 1 b 1 p 2 s 2 b 2 Offspring Individual 2

15 Crossover and mutation Individual 1 p 1 s 1 b 1 p 2 s 2 b 2 Random mutation Offspring Individual 2

16 Crossover and mutation Individual 1 p 1 s 1 b 1 p 2 s 2 b 2 Random mutation Offspring Individual 2

17 Crossover and mutation Individual 1 p 1 s 1 b 1 p 2 s 2 b 2 Offspring Individual 2

18 Crossover and mutation Individual 1 p 1 s 1 b 1 p 2 s 2 b 2 Offspring Individual 2

19 Crossover and mutation Individual 1 p 1 s 1 b 1 p 2 s 2 b 2 Offspring Individual 2 Random mutation

20 Crossover and mutation Individual 1 p 1 s 1 b 1 p 2 s 2 b 2 Offspring Copy Individual 2

21 Crossover and mutation Individual 1 p 1 s 1 b 1 p 2 s 2 b 2 Offspring p i s i b i Individual 2

22 Time dimension Training the behavioral vector during time using gradient algorithm. Age=0 p i s i b i Time

23 Time dimension Training the behavioral vector during time using gradient algorithm. Age=0 Age=1 p i s i b i Time

24 Time dimension Training the behavioral vector during time using gradient algorithm. Age=0 Age=1 Age=2 p i s i b i Time

25 Probability control Probability functions RP reproduction probability, DP death probability, elimination of bad solutions in population. Balancing functions to keep the population size in some reasonable limits.

26 Reproduction probability Raw reproduction probability function * * RP x i = RP a i, F x i Fitness RP* Age Fitness Age

27 Death probability Raw death probability function * * DP x i = DP a i, F x i Fitness DP* Age Fitness Age

28 Balancing functions Computation of final probabilities. Depend on raw probabilities and population size. Big population grows slower, small population grows faster. * RP x i = BAL RP N, RP x i * DP x i = BAL DP N, DP x i

29 Evolution control

30 Evolution control

31 Evolution control

32 Evolution control

33 Evolution control

34 Evolution control

35 Evolution control

36 Testing, experiments Construction of the neural networks. Universal topology based on fully recurrent network. Structure topology adjacency matrix activation functions parametrized Λ-functions Behavior weight matrix

37 Testing, experiments Neural networks based on fully recurrent topology construction using CEA Activation function optimization

38 Testing, experiments Benchmark tasks Learn to oscillate experiment

39 Population behavior

40 Population behavior

41 Fitness Population behavior Iterations

42 Conclusion Reduction of the number of fitness function evaluations. Using the probability and balancing functions it is possible to change the CEA to behave more like random search, standard genetic algorithm, or gradient algorithm.

43 Conclusion CEA universal optimization algorithm mainly for problems with separate description of structure and behavior typically neural networks. Automatic control of the size of the population exploitation exploration

Clustering Genetic Algorithm

Clustering Genetic Algorithm Clustering Genetic Algorithm Petra Kudová Department of Theoretical Computer Science Institute of Computer Science Academy of Sciences of the Czech Republic ETID 2007 Outline Introduction Clustering Genetic

More information

Hyperspectral Data Analysis and Supervised Feature Reduction Via Projection Pursuit

Hyperspectral Data Analysis and Supervised Feature Reduction Via Projection Pursuit Hyperspectral Data Analysis and Supervised Feature Reduction Via Projection Pursuit Medical Image Analysis Luis O. Jimenez and David A. Landgrebe Ion Marqués, Grupo de Inteligencia Computacional, UPV/EHU

More information

Integer Programming: Algorithms - 3

Integer Programming: Algorithms - 3 Week 9 Integer Programming: Algorithms - 3 OPR 992 Applied Mathematical Programming OPR 992 - Applied Mathematical Programming - p. 1/12 Dantzig-Wolfe Reformulation Example Strength of the Linear Programming

More information

Solving Timetable Scheduling Problem by Using Genetic Algorithms

Solving Timetable Scheduling Problem by Using Genetic Algorithms Solving Timetable Scheduling Problem by Using Genetic Algorithms Branimir Sigl, Marin Golub, Vedran Mornar Faculty of Electrical Engineering and Computing, University of Zagreb Unska 3, 1 Zagreb, Croatia

More information

Automatic parameter regulation for a tracking system with an auto-critical function

Automatic parameter regulation for a tracking system with an auto-critical function Automatic parameter regulation for a tracking system with an auto-critical function Daniela Hall INRIA Rhône-Alpes, St. Ismier, France Email: Daniela.Hall@inrialpes.fr Abstract In this article we propose

More information

Comparing Neural Networks and ARMA Models in Artificial Stock Market

Comparing Neural Networks and ARMA Models in Artificial Stock Market Comparing Neural Networks and ARMA Models in Artificial Stock Market Jiří Krtek Academy of Sciences of the Czech Republic, Institute of Information Theory and Automation. e-mail: krtek@karlin.mff.cuni.cz

More information

International Journal of Software and Web Sciences (IJSWS) www.iasir.net

International Journal of Software and Web Sciences (IJSWS) www.iasir.net International Association of Scientific Innovation and Research (IASIR) (An Association Unifying the Sciences, Engineering, and Applied Research) ISSN (Print): 2279-0063 ISSN (Online): 2279-0071 International

More information

Pattern recognition using multilayer neural-genetic algorithm

Pattern recognition using multilayer neural-genetic algorithm Neurocomputing 51 (2003) 237 247 www.elsevier.com/locate/neucom Pattern recognition using multilayer neural-genetic algorithm Yas Abbas Alsultanny, Musbah M. Aqel Computer Science Department, College o

More information

14.10.2014. Overview. Swarms in nature. Fish, birds, ants, termites, Introduction to swarm intelligence principles Particle Swarm Optimization (PSO)

14.10.2014. Overview. Swarms in nature. Fish, birds, ants, termites, Introduction to swarm intelligence principles Particle Swarm Optimization (PSO) Overview Kyrre Glette kyrrehg@ifi INF3490 Swarm Intelligence Particle Swarm Optimization Introduction to swarm intelligence principles Particle Swarm Optimization (PSO) 3 Swarms in nature Fish, birds,

More information

CHAPTER 3 SECURITY CONSTRAINED OPTIMAL SHORT-TERM HYDROTHERMAL SCHEDULING

CHAPTER 3 SECURITY CONSTRAINED OPTIMAL SHORT-TERM HYDROTHERMAL SCHEDULING 60 CHAPTER 3 SECURITY CONSTRAINED OPTIMAL SHORT-TERM HYDROTHERMAL SCHEDULING 3.1 INTRODUCTION Optimal short-term hydrothermal scheduling of power systems aims at determining optimal hydro and thermal generations

More information

Genetic Algorithm. Based on Darwinian Paradigm. Intrinsically a robust search and optimization mechanism. Conceptual Algorithm

Genetic Algorithm. Based on Darwinian Paradigm. Intrinsically a robust search and optimization mechanism. Conceptual Algorithm 24 Genetic Algorithm Based on Darwinian Paradigm Reproduction Competition Survive Selection Intrinsically a robust search and optimization mechanism Slide -47 - Conceptual Algorithm Slide -48 - 25 Genetic

More information

Load balancing in a heterogeneous computer system by self-organizing Kohonen network

Load balancing in a heterogeneous computer system by self-organizing Kohonen network Bull. Nov. Comp. Center, Comp. Science, 25 (2006), 69 74 c 2006 NCC Publisher Load balancing in a heterogeneous computer system by self-organizing Kohonen network Mikhail S. Tarkov, Yakov S. Bezrukov Abstract.

More information

College of information technology Department of software

College of information technology Department of software University of Babylon Undergraduate: third class College of information technology Department of software Subj.: Application of AI lecture notes/2011-2012 ***************************************************************************

More information

Memory Allocation Technique for Segregated Free List Based on Genetic Algorithm

Memory Allocation Technique for Segregated Free List Based on Genetic Algorithm Journal of Al-Nahrain University Vol.15 (2), June, 2012, pp.161-168 Science Memory Allocation Technique for Segregated Free List Based on Genetic Algorithm Manal F. Younis Computer Department, College

More information

Web Service Selection using Particle Swarm Optimization and Genetic Algorithms

Web Service Selection using Particle Swarm Optimization and Genetic Algorithms Web Service Selection using Particle Swarm Optimization and Genetic Algorithms Simone A. Ludwig Department of Computer Science North Dakota State University Fargo, ND, USA simone.ludwig@ndsu.edu Thomas

More information

Evaluation of Crossover Operator Performance in Genetic Algorithms with Binary Representation

Evaluation of Crossover Operator Performance in Genetic Algorithms with Binary Representation Evaluation of Crossover Operator Performance in Genetic Algorithms with Binary Representation Stjepan Picek, Marin Golub, and Domagoj Jakobovic Faculty of Electrical Engineering and Computing, Unska 3,

More information

Research on the Performance Optimization of Hadoop in Big Data Environment

Research on the Performance Optimization of Hadoop in Big Data Environment Vol.8, No.5 (015), pp.93-304 http://dx.doi.org/10.1457/idta.015.8.5.6 Research on the Performance Optimization of Hadoop in Big Data Environment Jia Min-Zheng Department of Information Engineering, Beiing

More information

DECISION TREE INDUCTION FOR FINANCIAL FRAUD DETECTION USING ENSEMBLE LEARNING TECHNIQUES

DECISION TREE INDUCTION FOR FINANCIAL FRAUD DETECTION USING ENSEMBLE LEARNING TECHNIQUES DECISION TREE INDUCTION FOR FINANCIAL FRAUD DETECTION USING ENSEMBLE LEARNING TECHNIQUES Vijayalakshmi Mahanra Rao 1, Yashwant Prasad Singh 2 Multimedia University, Cyberjaya, MALAYSIA 1 lakshmi.mahanra@gmail.com

More information

ISSN: 2319-5967 ISO 9001:2008 Certified International Journal of Engineering Science and Innovative Technology (IJESIT) Volume 2, Issue 3, May 2013

ISSN: 2319-5967 ISO 9001:2008 Certified International Journal of Engineering Science and Innovative Technology (IJESIT) Volume 2, Issue 3, May 2013 Transistor Level Fault Finding in VLSI Circuits using Genetic Algorithm Lalit A. Patel, Sarman K. Hadia CSPIT, CHARUSAT, Changa., CSPIT, CHARUSAT, Changa Abstract This paper presents, genetic based algorithm

More information

Multiple Layer Perceptron Training Using Genetic Algorithms

Multiple Layer Perceptron Training Using Genetic Algorithms Multiple Layer Perceptron Training Using Genetic Algorithms Udo Seiffert University of South Australia, Adelaide Knowledge-Based Intelligent Engineering Systems Centre (KES) Mawson Lakes, 5095, Adelaide,

More information

Feature Selection for Stock Market Analysis

Feature Selection for Stock Market Analysis Feature Selection for Stock Market Analysis Yuqinq He, Kamaladdin Fataliyev, and Lipo Wang School of Electrical and Electronic Engineering Nanyang Technological University Singapore Abstract. The analysis

More information

About the Author. The Role of Artificial Intelligence in Software Engineering. Brief History of AI. Introduction 2/27/2013

About the Author. The Role of Artificial Intelligence in Software Engineering. Brief History of AI. Introduction 2/27/2013 About the Author The Role of Artificial Intelligence in Software Engineering By: Mark Harman Presented by: Jacob Lear Mark Harman is a Professor of Software Engineering at University College London Director

More information

Cellular Automaton: The Roulette Wheel and the Landscape Effect

Cellular Automaton: The Roulette Wheel and the Landscape Effect Cellular Automaton: The Roulette Wheel and the Landscape Effect Ioan Hălălae Faculty of Engineering, Eftimie Murgu University, Traian Vuia Square 1-4, 385 Reşiţa, Romania Phone: +40 255 210227, Fax: +40

More information

New binary representation in Genetic Algorithms for solving TSP by mapping permutations to a list of ordered numbers

New binary representation in Genetic Algorithms for solving TSP by mapping permutations to a list of ordered numbers Proceedings of the 5th WSEAS Int Conf on COMPUTATIONAL INTELLIGENCE, MAN-MACHINE SYSTEMS AND CYBERNETICS, Venice, Italy, November 0-, 006 363 New binary representation in Genetic Algorithms for solving

More information

Alpha Cut based Novel Selection for Genetic Algorithm

Alpha Cut based Novel Selection for Genetic Algorithm Alpha Cut based Novel for Genetic Algorithm Rakesh Kumar Professor Girdhar Gopal Research Scholar Rajesh Kumar Assistant Professor ABSTRACT Genetic algorithm (GA) has several genetic operators that can

More information

A HYBRID GENETIC ALGORITHM FOR THE MAXIMUM LIKELIHOOD ESTIMATION OF MODELS WITH MULTIPLE EQUILIBRIA: A FIRST REPORT

A HYBRID GENETIC ALGORITHM FOR THE MAXIMUM LIKELIHOOD ESTIMATION OF MODELS WITH MULTIPLE EQUILIBRIA: A FIRST REPORT New Mathematics and Natural Computation Vol. 1, No. 2 (2005) 295 303 c World Scientific Publishing Company A HYBRID GENETIC ALGORITHM FOR THE MAXIMUM LIKELIHOOD ESTIMATION OF MODELS WITH MULTIPLE EQUILIBRIA:

More information

A Review And Evaluations Of Shortest Path Algorithms

A Review And Evaluations Of Shortest Path Algorithms A Review And Evaluations Of Shortest Path Algorithms Kairanbay Magzhan, Hajar Mat Jani Abstract: Nowadays, in computer networks, the routing is based on the shortest path problem. This will help in minimizing

More information

6. Feed-forward mapping networks

6. Feed-forward mapping networks 6. Feed-forward mapping networks Fundamentals of Computational Neuroscience, T. P. Trappenberg, 2002. Lecture Notes on Brain and Computation Byoung-Tak Zhang Biointelligence Laboratory School of Computer

More information

A Review of Data Mining Techniques

A Review of Data Mining Techniques Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology IJCSMC, Vol. 3, Issue. 4, April 2014,

More information

Genetic Algorithms. Part 2: The Knapsack Problem. Spring 2009 Instructor: Dr. Masoud Yaghini

Genetic Algorithms. Part 2: The Knapsack Problem. Spring 2009 Instructor: Dr. Masoud Yaghini Genetic Algorithms Part 2: The Knapsack Problem Spring 2009 Instructor: Dr. Masoud Yaghini Outline Genetic Algorithms: Part 2 Problem Definition Representations Fitness Function Handling of Constraints

More information

Inertia Weight Strategies in Particle Swarm Optimization

Inertia Weight Strategies in Particle Swarm Optimization Inertia Weight Strategies in Particle Swarm Optimization 1 J. C. Bansal, 2 P. K. Singh 3 Mukesh Saraswat, 4 Abhishek Verma, 5 Shimpi Singh Jadon, 6,7 Ajith Abraham 1,2,3,4,5 ABV-Indian Institute of Information

More information

Genetic Algorithm for Solving Simple Mathematical Equality Problem

Genetic Algorithm for Solving Simple Mathematical Equality Problem Genetic Algorithm for Solving Simple Mathematical Equality Problem Denny Hermawanto Indonesian Institute of Sciences (LIPI), INDONESIA Mail: denny.hermawanto@gmail.com Abstract This paper explains genetic

More information

Machine Learning and Data Analysis overview. Department of Cybernetics, Czech Technical University in Prague. http://ida.felk.cvut.

Machine 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 information

Keywords revenue management, yield management, genetic algorithm, airline reservation

Keywords revenue management, yield management, genetic algorithm, airline reservation Volume 4, Issue 1, January 2014 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com A Revenue Management

More information

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, VOL. 13, NO. 2, APRIL 2009 243

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, VOL. 13, NO. 2, APRIL 2009 243 IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, VOL. 13, NO. 2, APRIL 2009 243 Self-Adaptive Multimethod Search for Global Optimization in Real-Parameter Spaces Jasper A. Vrugt, Bruce A. Robinson, and James

More information

A Novel Binary Particle Swarm Optimization

A Novel Binary Particle Swarm Optimization Proceedings of the 5th Mediterranean Conference on T33- A Novel Binary Particle Swarm Optimization Motaba Ahmadieh Khanesar, Member, IEEE, Mohammad Teshnehlab and Mahdi Aliyari Shoorehdeli K. N. Toosi

More information

Architectural Design for Space Layout by Genetic Algorithms

Architectural Design for Space Layout by Genetic Algorithms Architectural Design for Space Layout by Genetic Algorithms Özer Ciftcioglu, Sanja Durmisevic and I. Sevil Sariyildiz Delft University of Technology, Faculty of Architecture Building Technology, 2628 CR

More information

Original Article Efficient Genetic Algorithm on Linear Programming Problem for Fittest Chromosomes

Original Article Efficient Genetic Algorithm on Linear Programming Problem for Fittest Chromosomes International Archive of Applied Sciences and Technology Volume 3 [2] June 2012: 47-57 ISSN: 0976-4828 Society of Education, India Website: www.soeagra.com/iaast/iaast.htm Original Article Efficient Genetic

More information

PERFORMANCE ANALYSIS OF HYBRID FORECASTING MODEL IN STOCK MARKET FORECASTING

PERFORMANCE ANALYSIS OF HYBRID FORECASTING MODEL IN STOCK MARKET FORECASTING PERFORMANCE ANALYSIS OF HYBRID FORECASTING MODEL IN STOCK MARKET FORECASTING Mahesh S. Khadka*, K. M. George, N. Park and J. B. Kim a Department of Computer Science, Oklahoma State University, Stillwater,

More information

A Simultaneous Solution for General Linear Equations on a Ring or Hierarchical Cluster

A Simultaneous Solution for General Linear Equations on a Ring or Hierarchical Cluster Acta Technica Jaurinensis Vol. 3. No. 1. 010 A Simultaneous Solution for General Linear Equations on a Ring or Hierarchical Cluster G. Molnárka, N. Varjasi Széchenyi István University Győr, Hungary, H-906

More information

PLAANN as a Classification Tool for Customer Intelligence in Banking

PLAANN as a Classification Tool for Customer Intelligence in Banking PLAANN as a Classification Tool for Customer Intelligence in Banking EUNITE World Competition in domain of Intelligent Technologies The Research Report Ireneusz Czarnowski and Piotr Jedrzejowicz Department

More information

Flexible Neural Trees Ensemble for Stock Index Modeling

Flexible Neural Trees Ensemble for Stock Index Modeling Flexible Neural Trees Ensemble for Stock Index Modeling Yuehui Chen 1, Ju Yang 1, Bo Yang 1 and Ajith Abraham 2 1 School of Information Science and Engineering Jinan University, Jinan 250022, P.R.China

More information

Filling the Semantic Gap: A Genetic Programming Framework for Content-Based Image Retrieval

Filling the Semantic Gap: A Genetic Programming Framework for Content-Based Image Retrieval INSTITUTE OF COMPUTING University of Campinas Filling the Semantic Gap: A Genetic Programming Framework for Content-Based Image Retrieval Ricardo da Silva Torres rtorres@ic.unicamp.br www.ic.unicamp.br/~rtorres

More information

Evolutionary SAT Solver (ESS)

Evolutionary SAT Solver (ESS) Ninth LACCEI Latin American and Caribbean Conference (LACCEI 2011), Engineering for a Smart Planet, Innovation, Information Technology and Computational Tools for Sustainable Development, August 3-5, 2011,

More information

Skill-based Resource Allocation using Genetic Algorithms and Ontologies

Skill-based Resource Allocation using Genetic Algorithms and Ontologies Skill-based Resource Allocation using Genetic Algorithms and Ontologies Kushan Nammuni 1, John Levine 2 & John Kingston 2 1 Department of Biomedical Informatics, Eastman Institute for Oral Health Care

More information

CLOUD DATABASE ROUTE SCHEDULING USING COMBANATION OF PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM

CLOUD DATABASE ROUTE SCHEDULING USING COMBANATION OF PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM CLOUD DATABASE ROUTE SCHEDULING USING COMBANATION OF PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM *Shabnam Ghasemi 1 and Mohammad Kalantari 2 1 Deparment of Computer Engineering, Islamic Azad University,

More information

GAMEPLAY-BASED OPTIMIZATION OF A SIMPLE 2D SIDE-SCROLLING MOBILE GAME USING ARTIFICIAL EVOLUTION EU CHUN VUI

GAMEPLAY-BASED OPTIMIZATION OF A SIMPLE 2D SIDE-SCROLLING MOBILE GAME USING ARTIFICIAL EVOLUTION EU CHUN VUI GAMEPLAY-BASED OPTIMIZATION OF A SIMPLE 2D SIDE-SCROLLING MOBILE GAME USING ARTIFICIAL EVOLUTION EU CHUN VUI FACULTY OF COMPUTING AND INFORMATICS UNIVERSITY MALAYSIA SABAH 2015 ABSTRACT Evolutionary Computing

More information

SOFT COMPUTING AND ITS USE IN RISK MANAGEMENT

SOFT COMPUTING AND ITS USE IN RISK MANAGEMENT SOFT COMPUTING AND ITS USE IN RISK MANAGEMENT doc. Ing. Petr Dostál, CSc. Brno University of Technology, Kolejní 4, 612 00 Brno, Czech Republic, Institute of Informatics, Faculty of Business and Management,

More information

Stock price prediction using genetic algorithms and evolution strategies

Stock price prediction using genetic algorithms and evolution strategies Stock price prediction using genetic algorithms and evolution strategies Ganesh Bonde Institute of Artificial Intelligence University Of Georgia Athens,GA-30601 Email: ganesh84@uga.edu Rasheed Khaled Institute

More information

Asexual Versus Sexual Reproduction in Genetic Algorithms 1

Asexual Versus Sexual Reproduction in Genetic Algorithms 1 Asexual Versus Sexual Reproduction in Genetic Algorithms Wendy Ann Deslauriers (wendyd@alumni.princeton.edu) Institute of Cognitive Science,Room 22, Dunton Tower Carleton University, 25 Colonel By Drive

More information

Computational Hybrids Towards Software Defect Predictions

Computational Hybrids Towards Software Defect Predictions Abstract International Journal of Scientific Engineering and Technology (ISSN : 2277-1581) Computational Hybrids Towards Software Defect Predictions Manu Banga Department of Computer Sciences and Engineering,

More information

Feature Selection using Integer and Binary coded Genetic Algorithm to improve the performance of SVM Classifier

Feature Selection using Integer and Binary coded Genetic Algorithm to improve the performance of SVM Classifier Feature Selection using Integer and Binary coded Genetic Algorithm to improve the performance of SVM Classifier D.Nithya a, *, V.Suganya b,1, R.Saranya Irudaya Mary c,1 Abstract - This paper presents,

More information

A Brief Study of the Nurse Scheduling Problem (NSP)

A Brief Study of the Nurse Scheduling Problem (NSP) A Brief Study of the Nurse Scheduling Problem (NSP) Lizzy Augustine, Morgan Faer, Andreas Kavountzis, Reema Patel Submitted Tuesday December 15, 2009 0. Introduction and Background Our interest in the

More information

The Applications of Genetic Algorithms in Stock Market Data Mining Optimisation

The Applications of Genetic Algorithms in Stock Market Data Mining Optimisation The Applications of Genetic Algorithms in Stock Market Data Mining Optimisation Li Lin, Longbing Cao, Jiaqi Wang, Chengqi Zhang Faculty of Information Technology, University of Technology, Sydney, NSW

More information

Optimal PID Controller Design for AVR System

Optimal PID Controller Design for AVR System Tamkang Journal of Science and Engineering, Vol. 2, No. 3, pp. 259 270 (2009) 259 Optimal PID Controller Design for AVR System Ching-Chang Wong*, Shih-An Li and Hou-Yi Wang Department of Electrical Engineering,

More information

Research on a Heuristic GA-Based Decision Support System for Rice in Heilongjiang Province

Research on a Heuristic GA-Based Decision Support System for Rice in Heilongjiang Province Research on a Heuristic GA-Based Decision Support System for Rice in Heilongjiang Province Ran Cao 1,1, Yushu Yang 1, Wei Guo 1, 1 Engineering college of Northeast Agricultural University, Haerbin, China

More information

Introduction to Machine Learning and Data Mining. Prof. Dr. Igor Trajkovski trajkovski@nyus.edu.mk

Introduction to Machine Learning and Data Mining. Prof. Dr. Igor Trajkovski trajkovski@nyus.edu.mk Introduction to Machine Learning and Data Mining Prof. Dr. Igor Trakovski trakovski@nyus.edu.mk Neural Networks 2 Neural Networks Analogy to biological neural systems, the most robust learning systems

More information

Genetic algorithms for changing environments

Genetic algorithms for changing environments Genetic algorithms for changing environments John J. Grefenstette Navy Center for Applied Research in Artificial Intelligence, Naval Research Laboratory, Washington, DC 375, USA gref@aic.nrl.navy.mil Abstract

More information

Practical Applications of Evolutionary Computation to Financial Engineering

Practical Applications of Evolutionary Computation to Financial Engineering Hitoshi Iba and Claus C. Aranha Practical Applications of Evolutionary Computation to Financial Engineering Robust Techniques for Forecasting, Trading and Hedging 4Q Springer Contents 1 Introduction to

More information

Vol. 35, No. 3, Sept 30,2000 ملخص تعتبر الخوارزمات الجينية واحدة من أفضل طرق البحث من ناحية األداء. فبالرغم من أن استخدام هذه الطريقة ال يعطي الحل

Vol. 35, No. 3, Sept 30,2000 ملخص تعتبر الخوارزمات الجينية واحدة من أفضل طرق البحث من ناحية األداء. فبالرغم من أن استخدام هذه الطريقة ال يعطي الحل AIN SHAMS UNIVERSITY FACULTY OF ENGINEERING Vol. 35, No. 3, Sept 30,2000 SCIENTIFIC BULLETIN Received on : 3/9/2000 Accepted on: 28/9/2000 pp : 337-348 GENETIC ALGORITHMS AND ITS USE WITH BACK- PROPAGATION

More information

Czech Technical University in Prague Faculty of Electrical Engineering. using. Pavel Kordík

Czech Technical University in Prague Faculty of Electrical Engineering. using. Pavel Kordík Czech Technical University in Prague Faculty of Electrical Engineering Fully Automated Knowledge Extraction using Group of Adaptive Models Evolution by Pavel Kordík A thesis submitted to the Faculty of

More information

ARAM ZINZALIAN, DEYAN SIMEONOV, AND ELINA ROBEVA

ARAM ZINZALIAN, DEYAN SIMEONOV, AND ELINA ROBEVA FX FORECASTING WITH HYBRID SUPPORT VECTOR MACHINES ARAM ZINZALIAN, DEYAN SIMEONOV, AND ELINA ROBEVA 1 Introduction Foreign exchange rates are notoriously difficult to predict Deciding which of thousands

More information

Model-based Parameter Optimization of an Engine Control Unit using Genetic Algorithms

Model-based Parameter Optimization of an Engine Control Unit using Genetic Algorithms Symposium on Automotive/Avionics Avionics Systems Engineering (SAASE) 2009, UC San Diego Model-based Parameter Optimization of an Engine Control Unit using Genetic Algorithms Dipl.-Inform. Malte Lochau

More information

A Hybrid Tabu Search Method for Assembly Line Balancing

A Hybrid Tabu Search Method for Assembly Line Balancing Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization, Beijing, China, September 15-17, 2007 443 A Hybrid Tabu Search Method for Assembly Line Balancing SUPAPORN

More information

Genetic algorithm evolved agent-based equity trading using Technical Analysis and the Capital Asset Pricing Model

Genetic algorithm evolved agent-based equity trading using Technical Analysis and the Capital Asset Pricing Model Genetic algorithm evolved agent-based equity trading using Technical Analysis and the Capital Asset Pricing Model Cyril Schoreels and Jonathan M. Garibaldi Automated Scheduling, Optimisation and Planning

More information

Research Article Service Composition Optimization Using Differential Evolution and Opposition-based Learning

Research Article Service Composition Optimization Using Differential Evolution and Opposition-based Learning Research Journal of Applied Sciences, Engineering and Technology 11(2): 229-234, 2015 ISSN: 2040-7459; e-issn: 2040-7467 2015 Maxwell Scientific Publication Corp. Submitted: May 20, 2015 Accepted: June

More information

Performance Optimization of I-4 I 4 Gasoline Engine with Variable Valve Timing Using WAVE/iSIGHT

Performance Optimization of I-4 I 4 Gasoline Engine with Variable Valve Timing Using WAVE/iSIGHT Performance Optimization of I-4 I 4 Gasoline Engine with Variable Valve Timing Using WAVE/iSIGHT Sean Li, DaimlerChrysler (sl60@dcx dcx.com) Charles Yuan, Engineous Software, Inc (yuan@engineous.com) Background!

More information

STA 4273H: Statistical Machine Learning

STA 4273H: Statistical Machine Learning STA 4273H: Statistical Machine Learning Russ Salakhutdinov Department of Statistics! rsalakhu@utstat.toronto.edu! http://www.cs.toronto.edu/~rsalakhu/ Lecture 6 Three Approaches to Classification Construct

More information

Numerical Research on Distributed Genetic Algorithm with Redundant

Numerical Research on Distributed Genetic Algorithm with Redundant Numerical Research on Distributed Genetic Algorithm with Redundant Binary Number 1 Sayori Seto, 2 Akinori Kanasugi 1,2 Graduate School of Engineering, Tokyo Denki University, Japan 10kme41@ms.dendai.ac.jp,

More information

Genetic Algorithm based Approach to Solve Non Fractional (0/1) Knapsack Optimization Problem

Genetic Algorithm based Approach to Solve Non Fractional (0/1) Knapsack Optimization Problem Genetic Algorithm based Approach to Solve Non Fractional (0/1) Knapsack Optimization Problem Vikas Thada Asst. Prof (CSE), ASET, Amity University, Gurgaon, India Shivali Dhaka Asst. Prof (CSE), ASET, Amity

More information

An Overview of Knowledge Discovery Database and Data mining Techniques

An 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 information

A Basic Guide to Modeling Techniques for All Direct Marketing Challenges

A Basic Guide to Modeling Techniques for All Direct Marketing Challenges A Basic Guide to Modeling Techniques for All Direct Marketing Challenges Allison Cornia Database Marketing Manager Microsoft Corporation C. Olivia Rud Executive Vice President Data Square, LLC Overview

More information

Introduction to Machine Learning. Speaker: Harry Chao Advisor: J.J. Ding Date: 1/27/2011

Introduction to Machine Learning. Speaker: Harry Chao Advisor: J.J. Ding Date: 1/27/2011 Introduction to Machine Learning Speaker: Harry Chao Advisor: J.J. Ding Date: 1/27/2011 1 Outline 1. What is machine learning? 2. The basic of machine learning 3. Principles and effects of machine learning

More information

The QOOL Algorithm for fast Online Optimization of Multiple Degree of Freedom Robot Locomotion

The QOOL Algorithm for fast Online Optimization of Multiple Degree of Freedom Robot Locomotion The QOOL Algorithm for fast Online Optimization of Multiple Degree of Freedom Robot Locomotion Daniel Marbach January 31th, 2005 Swiss Federal Institute of Technology at Lausanne Daniel.Marbach@epfl.ch

More information

Neural Networks. Introduction to Artificial Intelligence CSE 150 May 29, 2007

Neural Networks. Introduction to Artificial Intelligence CSE 150 May 29, 2007 Neural Networks Introduction to Artificial Intelligence CSE 150 May 29, 2007 Administration Last programming assignment has been posted! Final Exam: Tuesday, June 12, 11:30-2:30 Last Lecture Naïve Bayes

More information

A Hybrid Machine Learning System for Stock Market Forecasting

A Hybrid Machine Learning System for Stock Market Forecasting Journal of International Technology and Information Management Volume 20 Issue 1 Double Issue 1/2 Article 3 2011 A Hybrid Machine Learning System for Stock Market Forecasting Lokesh Kumar Babu Banarasi

More information

Constrained Classification of Large Imbalanced Data by Logistic Regression and Genetic Algorithm

Constrained Classification of Large Imbalanced Data by Logistic Regression and Genetic Algorithm Constrained Classification of Large Imbalanced Data by Logistic Regression and Genetic Algorithm Martin Hlosta, Rostislav Stríž, Jan Kupčík, Jaroslav Zendulka, and Tomáš Hruška A. Imbalanced Data Classification

More information

Internal Evolution for Agent Cognition Agent-Based Modelling of an Artificial Stock Market

Internal Evolution for Agent Cognition Agent-Based Modelling of an Artificial Stock Market Internal Evolution for Agent Cognition Agent-Based Modelling of an Artificial Stock Market Master of Science Thesis in Complex Adaptive Systems MORTEZA HASSANZADEH Department of Energy and Environment

More information

GARDA: a Diagnostic ATPG for Large Synchronous Sequential Circuits

GARDA: a Diagnostic ATPG for Large Synchronous Sequential Circuits GARDA: a Diagnostic ATPG for Large Synchronous Sequential Circuits F. Corno, P. Prinetto, M. Rebaudengo, M. Sonza Reorda Politecnico di Torino Dipartimento di Automatica e Informatica Torino, Italy Abstract

More information

Neural Networks Kohonen Self-Organizing Maps

Neural Networks Kohonen Self-Organizing Maps Neural Networks Kohonen Self-Organizing Maps Mohamed Krini Christian-Albrechts-Universität zu Kiel Faculty of Engineering Institute of Electrical and Information Engineering Digital Signal Processing and

More information

A Brief Introduction to Systems Biology: Gene Regulatory Networks Rajat K. De

A Brief Introduction to Systems Biology: Gene Regulatory Networks Rajat K. De A Brief Introduction to Systems Biology: Gene Regulatory Networks Rajat K. De Machine Intelligence Unit, Indian Statistical Institute 203 B. T. Road Kolkata 700108 email id: rajat@isical.ac.in 1 Informatics

More information

Hybrid processing of SCADA and synchronized phasor measurements for tracking network state

Hybrid processing of SCADA and synchronized phasor measurements for tracking network state IEEE PES General Meeting, Denver, USA, July 2015 1 Hybrid processing of SCADA and synchronized phasor measurements for tracking network state Boris Alcaide-Moreno Claudio Fuerte-Esquivel Universidad Michoacana

More information

NEURAL NETWORK FUNDAMENTALS WITH GRAPHS, ALGORITHMS, AND APPLICATIONS

NEURAL NETWORK FUNDAMENTALS WITH GRAPHS, ALGORITHMS, AND APPLICATIONS NEURAL NETWORK FUNDAMENTALS WITH GRAPHS, ALGORITHMS, AND APPLICATIONS N. K. Bose HRB-Systems Professor of Electrical Engineering The Pennsylvania State University, University Park P. Liang Associate Professor

More information

Dynamic Task Scheduling with Load Balancing using Hybrid Particle Swarm Optimization

Dynamic Task Scheduling with Load Balancing using Hybrid Particle Swarm Optimization Int. J. Open Problems Compt. Math., Vol. 2, No. 3, September 2009 ISSN 1998-6262; Copyright ICSRS Publication, 2009 www.i-csrs.org Dynamic Task Scheduling with Load Balancing using Hybrid Particle Swarm

More information

Course 803401 DSS. Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization

Course 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 information

Agenda. Project Green@Cloud Done Work In-progress Work Future Work

Agenda. Project Green@Cloud Done Work In-progress Work Future Work Agenda Project Green@Cloud Done Work In-progress Work Future Work Project Green@Cloud Multi-objective meta-heuristics for energy-aware scheduling in cloud computing systems Publications Paper for the special

More information

THREE DIMENSIONAL REPRESENTATION OF AMINO ACID CHARAC- TERISTICS

THREE DIMENSIONAL REPRESENTATION OF AMINO ACID CHARAC- TERISTICS THREE DIMENSIONAL REPRESENTATION OF AMINO ACID CHARAC- TERISTICS O.U. Sezerman 1, R. Islamaj 2, E. Alpaydin 2 1 Laborotory of Computational Biology, Sabancı University, Istanbul, Turkey. 2 Computer Engineering

More information

Research of distributed IDS based on mobile agent and genetic algorithm

Research of distributed IDS based on mobile agent and genetic algorithm Research of distributed IDS based on mobile agent and genetic algorithm Abstract Weimin Gao 1*, Lizhen Xiao 2 1 School of computer and information science, Hunan institute of technology, Heng yang 421002,

More information

Genetic Algorithm Based Interconnection Network Topology Optimization Analysis

Genetic Algorithm Based Interconnection Network Topology Optimization Analysis Genetic Algorithm Based Interconnection Network Topology Optimization Analysis 1 WANG Peng, 2 Wang XueFei, 3 Wu YaMing 1,3 College of Information Engineering, Suihua University, Suihua Heilongjiang, 152061

More information

A hybrid Approach of Genetic Algorithm and Particle Swarm Technique to Software Test Case Generation

A hybrid Approach of Genetic Algorithm and Particle Swarm Technique to Software Test Case Generation A hybrid Approach of Genetic Algorithm and Particle Swarm Technique to Software Test Case Generation Abhishek Singh Department of Information Technology Amity School of Engineering and Technology Amity

More information

Estimation of the COCOMO Model Parameters Using Genetic Algorithms for NASA Software Projects

Estimation of the COCOMO Model Parameters Using Genetic Algorithms for NASA Software Projects Journal of Computer Science 2 (2): 118-123, 2006 ISSN 1549-3636 2006 Science Publications Estimation of the COCOMO Model Parameters Using Genetic Algorithms for NASA Software Projects Alaa F. Sheta Computers

More information

Data Mining and Pattern Recognition for Large-Scale Scientific Data

Data Mining and Pattern Recognition for Large-Scale Scientific Data Data Mining and Pattern Recognition for Large-Scale Scientific Data Chandrika Kamath Center for Applied Scientific Computing Lawrence Livermore National Laboratory October 15, 1998 We need an effective

More information

A Genetic Programming Model for S&P 500 Stock Market Prediction

A Genetic Programming Model for S&P 500 Stock Market Prediction Vol.6, No.5 (2013), pp.303-314 http://dx.doi.org/10.14257/ijca.2013.6.6.29 A Genetic Programming Model for S&P 500 Stock Market Prediction Alaa Sheta, Hossam Faris, Mouhammd Alkasassbeh Abstract The stock

More information

Introduction To Genetic Algorithms

Introduction To Genetic Algorithms 1 Introduction To Genetic Algorithms Dr. Rajib Kumar Bhattacharjya Department of Civil Engineering IIT Guwahati Email: rkbc@iitg.ernet.in References 2 D. E. Goldberg, Genetic Algorithm In Search, Optimization

More information

SELECTING NEURAL NETWORK ARCHITECTURE FOR INVESTMENT PROFITABILITY PREDICTIONS

SELECTING NEURAL NETWORK ARCHITECTURE FOR INVESTMENT PROFITABILITY PREDICTIONS UDC: 004.8 Original scientific paper SELECTING NEURAL NETWORK ARCHITECTURE FOR INVESTMENT PROFITABILITY PREDICTIONS Tonimir Kišasondi, Alen Lovren i University of Zagreb, Faculty of Organization and Informatics,

More information

2: Computer Performance

2: Computer Performance 2: Computer Performance http://people.sc.fsu.edu/ jburkardt/presentations/ fdi 2008 lecture2.pdf... John Information Technology Department Virginia Tech... FDI Summer Track V: Parallel Programming 10-12

More information

Design of Web Ranking Module using Genetic Algorithm

Design of Web Ranking Module using Genetic Algorithm Design of Web Ranking Module using Genetic Algorithm Vikas Thada Research Scholar Dr.K.N.M. University Newai, India Vivek Jaglan, Ph.D Asst.Prof(CSE),ASET Amity University Gurgaon, India ABSTRACT Crawling

More information

Neural Network and Genetic Algorithm Based Trading Systems. Donn S. Fishbein, MD, PhD Neuroquant.com

Neural Network and Genetic Algorithm Based Trading Systems. Donn S. Fishbein, MD, PhD Neuroquant.com Neural Network and Genetic Algorithm Based Trading Systems Donn S. Fishbein, MD, PhD Neuroquant.com Consider the challenge of constructing a financial market trading system using commonly available technical

More information

Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization

Chapter 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 information

A Genetic Algorithm Processor Based on Redundant Binary Numbers (GAPBRBN)

A Genetic Algorithm Processor Based on Redundant Binary Numbers (GAPBRBN) ISSN: 2278 1323 All Rights Reserved 2014 IJARCET 3910 A Genetic Algorithm Processor Based on Redundant Binary Numbers (GAPBRBN) Miss: KIRTI JOSHI Abstract A Genetic Algorithm (GA) is an intelligent search

More information