Genetic Programming - New Approaches and Successful Applications ppt

GENETIC PROGRAMMING – NEW APPROACHES AND SUCCESSFUL APPLICATIONS Edited by Sebastián Ventura Genetic Programming – New Approaches and Successful Applications http://dx.doi.org/10.5772/3102 Edited by Sebastián Ventura Contributors Uday Kamath, Jeffrey K. Bassett, Kenneth A. De Jong, Cyril Fonlupt, Denis Robilliard, Virginie Marion-Poty, Yoshihiko Hasegawa, Guilherme Esmeraldo, Robson Feitosa, Dilza Esmeraldo , Edna Barros, Douglas A. Augusto, Heder S. Bernardino, Helio J.C. Barbosa, Giovanni Andrea Casula, Giuseppe Mazzarella, Fathi Abid, Wafa Abdelmalek, Sana Ben Hamida, Polona Dobnik Dubrovski, Miran Brezočnik, Shreenivas N. Londhe, Pradnya R. Dixit, J. Sreekanth, Bithin Datta, M.L. Arganis, R. Val, R. Domínguez, K. Rodríguez, J. Dolz, J.M. Eaton, M. A. Ghorbani, R. Khatibi, H. Asadi and P. Yousefi Published by InTech Janeza Trdine 9, 51000 Rijeka, Croatia Copyright © 2012 InTech All chapters are Open Access distributed under the Creative Commons Attribution 3.0 license, which allows users to download, copy and build upon published articles even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. After this work has been published by InTech, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work. Any republication, referencing or personal use of the work must explicitly identify the original source. Notice Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Publishing Process Manager Marijan Polic Typesetting InTech Prepress, Novi Sad Cover InTech Design Team First published October, 2012 Printed in Croatia A free online edition of this book is available at www.intechopen.com Additional hard copies can be obtained from orders@intechopen.com Genetic Programming – New Approaches and Successful Applications, Edited by Sebastián Ventura p. cm. ISBN 978-953-51-0809-2 Contents Preface IX Section 1 New Approaches 1 Chapter 1 Using Quantitative Genetics and Phenotypic Traits in Genetic Programming 3 Uday Kamath, Jeffrey K. Bassett and Kenneth A. De Jong Chapter 2 Continuous Schemes for Program Evolution 27 Cyril Fonlupt, Denis Robilliard and Virginie Marion-Poty Chapter 3 Programming with Annotated Grammar Estimation 49 Yoshihiko Hasegawa Chapter 4 Genetically Programmed Regression Linear Models for Non-Deterministic Estimates 75 Guilherme Esmeraldo, Robson Feitosa, Dilza Esmeraldo and Edna Barros Chapter 5 Parallel Genetic Programming on Graphics Processing Units 95 Douglas A. Augusto, Heder S. Bernardino and Helio J.C. Barbosa Section 2 Successful Applications 115 Chapter 6 Structure-Based Evolutionary Design Applied to Wire Antennas 117 Giovanni Andrea Casula and Giuseppe Mazzarella Chapter 7 Dynamic Hedging Using Generated Genetic Programming Implied Volatility Models 141 Fathi Abid, Wafa Abdelmalek and Sana Ben Hamida Chapter 8 The Usage of Genetic Methods for Prediction of Fabric Porosity 171 Polona Dobnik Dubrovski and Miran Brezočnik VI Contents Chapter 9 Genetic Programming: A Novel Computing Approach in Modeling Water Flows 199 Shreenivas N. Londhe and Pradnya R. Dixit Chapter 10 Genetic Programming: Efficient Modeling Tool in Hydrology and Groundwater Management 225 J. Sreekanth and Bithin Datta Chapter 11 Comparison Between Equations Obtained by Means of Multiple Linear Regression and Genetic Programming to Approach Measured Climatic Data in a River 239 M.L. Arganis, R. Val, R. Domínguez, K. Rodríguez, J. Dolz and J.M. Eaton Chapter 12 Inter-Comparison of an Evolutionary Programming Model of Suspended Sediment Time-Series with Other Local Models 255 M. A. Ghorbani, R. Khatibi, H. Asadi and P. Yousefi Preface Genetic programming (GP) is a branch of Evolutionary Computing that aims the automatic discovery of programs to solve a given problem. Since its appearance, in the earliest nineties, GP has become one of the most promising paradigms for solving problems in the artificial intelligence field, producing a number of human-competitive results and even patentable new inventions. And, as other areas in Computer Science, GP continues evolving quickly, with new ideas, techniques and applications being constantly proposed. The purpose of this book is to show recent advances in the field of GP, both the development of new theoretical approaches and the emergence of applications that have successfully solved different real world problems. It consists of twelve openly solicited chapters, written by international researchers and leading experts in the field of GP. The book is organized in two sections. The first section (chapters 1 to 5) introduces a new theoretical framework (the use of quantitative genetics and phenotypic traits – chapter 1) to analyse the behaviour of GP algorithms. Furthermore, the section contains three new GP proposals: the first one is based on the use of continuous values for the representation of programs (chapter 2), the second is based on the use of estimation of distribution algorithms (chapter 3), and the third hybridizes the use of GP with statistical models in order to obtain and formally validate linear regression models (chapter 4). The section ends with a nice introduction about the implementation of GP algorithms on graphics processing units (chapter 5). The second section of the book (chapters 6 to 12) shows several successful examples of the application of GP to several complex real-world problems. First of these applications is the use of GP in the automatic design of wireless antennas (chapter 6). The two following chapters show two interesting examples of industrial applications: the forecasting of the volatility of materials (chapter 7) and the prediction of fabric porosity (chapter 8). In both chapters GP models outperformed the results yield by the state-of-the art methods. The next three chapters are related to the application of GP to modelling water flows, being the first of them a gentle introduction to the topic (chapter 9) and the following two remarkable case studies (chapters 10 and 11). The last chapter of the book (chapter 12) shows the application of GP to an interesting time X Preface series modelling problem: the estimation of suspended sediment loads in the Mississippi river. The volume is primarily aimed at postgraduates, researchers and academics. Nevertheless, it is hoped that it may be useful to undergraduates who wish to learn about the leading techniques in GP. Sebastián Ventura Department of Computers Science and Numerical Analysis, University of Cordoba, Spain . GENETIC PROGRAMMING – NEW APPROACHES AND SUCCESSFUL APPLICATIONS Edited by Sebastián Ventura Genetic Programming – New Approaches and Successful Applications. Genetic Programming – New Approaches and Successful Applications, Edited by Sebastián Ventura p. cm. ISBN 97 8-9 5 3-5 1-0 80 9-2 Contents Preface IX Section 1 New Approaches. landscape and reproductive operators is needed in order to analyze an EA. Still, this approach has some 4 Genetic Programming – New Approaches and Successful Applications Using Quantitative Genetics and