-------- Original-Nachricht -------- Betreff: [computational.science] Engineering Evolutionary Intelligent Systems Datum: Sun, 21 Oct 2007 08:41:59 +0200 Von: Ajith Abraham ajith.abraham@ieee.org Antwort an: abraham.ajith@gmail.com Organisation: "OptimaNumerics" An: Computational Science Mailing List computational.science@lists.optimanumerics.com Referenzen: 736f122e0710150920h2dc094c2ua893572169611828@mail.gmail.com 736f122e0710202339g72a4bd05w3451d0fc5b12189e@mail.gmail.com
-- New Book Release --
*Engineering Evolutionary Intelligent Systems* ** Series: Studies in Computational Intelligence , Vol. 82 Editors: Ajith Abraham, Crina Grosan, Witold Pedrycz Approx. 400 p., Hardcover ISBN: 978-3-540-75395-7 http://www.springer.com/east/home/engineering?SGWID=5-175-22-173762620-0
Evolutionary design of intelligent systems is gaining much popularity due to its capabilities in handling several real world problems involving optimization, complexity, noisy and non-stationary environment, imprecision, uncertainty and vagueness. This edited volume 'Engineering Evolutionary Intelligent Systems' deals with the theoretical and methodological aspects, as well as various evolutionary algorithm applications to many real world problems originating from science, technology, business or commerce. This volume comprises of 15 chapters including an introductory chapter which covers the fundamental definitions and outlines some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.
Table of contents
Preface: http://www.softcomputing.net/eeis-preface.pdf
Engineering Evolutionary Intelligent Systems: Methodologies, Architectures and Reviews -- Ajith Abraham and Crina Grosan http://www.softcomputing.net/eeis.pdf
Genetically Optimized Hybrid Fuzzy Neural Networks: Analysis and Design of Rule-based Multi-layer Perceptron Architectures -- Sung-Kwun Oh and Witold Pedrycz
Genetically Optimized Self-organizing Neural Networks Based on Polynomial and Fuzzy Polynomial Neurons: Analysis and Design -- Sung-Kwun Oh and Witold Pedrycz
Evolution of Inductive Self-organizing Networks -- Dongwon Kim and Gwi-Tae Park
Recursive Pattern based Hybrid Supervised Training -- Kiruthika Ramanathan and Sheng Uei Guan
Enhancing Recursive Supervised Learning Using Clustering and Combinatorial Optimization (RSL-CC) -- Kiruthika Ramanathan and Sheng Uei Guan
Evolutionary Approaches to Rule Extraction from Neural Networks -- Urszula Markowska-Kaczmar
Cluster-wise Design of Takagi and Sugeno Approach of Fuzzy Logic Controller -- Tushar and Dilip Kumar Pratihar
Evolutionary Fuzzy Modelling for Drug Resistant HIV-1 Treatment Optimization -- Mattia Prosperi and Giovanni Ulivi
A New Genetic Approach for Neural Network Design -- Antonia Azzini and Andrea G.B. Tettamanzi
A Grammatical Genetic Programming Representation for Radial Basis Function Networks -- Ian Dempsey, Anthony Brabazon, and Michael O'Neill
A Neural-Genetic Technique for Coastal Engineering: Determining Wave-induced Seabed Liquefaction Depth -- Daeho Cha, Michael Blumenstein, Hong Zhang, and Dong-Sheng Jeng
On the Design of Large-scale Cellular Mobile Networks Using Multi-population Memetic Algorithms -- Alejandro Quintero and Samuel Pierre
A Hybrid Cellular Genetic Algorithm for the Capacitated Vehicle Routing Problem -- Enrique Alba and Bernab´e Dorronsoro
Particle Swarm Optimization with Mutation for High Dimensional Problems -- Jeff Achtnig
More book information: http://www.softcomputing.net/cec06/
http://www.springer.com/east/home/engineering?SGWID=5-175-22-173762620-0