Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence / Edition 2

Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence / Edition 2

by Candida Ferreira
     
 

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ISBN-10: 3642069320

ISBN-13: 9783642069321

Pub. Date: 10/31/2014

Publisher: Springer Berlin Heidelberg

Cândida Ferreira thoroughly describes the basic ideas of gene expression programming (GEP) and numerous modifications to this powerful new algorithm. This monograph provides all the implementation details of GEP so that anyone with elementary programming skills will be able to implement it themselves. The book also includes a self-contained introduction to

Overview

Cândida Ferreira thoroughly describes the basic ideas of gene expression programming (GEP) and numerous modifications to this powerful new algorithm. This monograph provides all the implementation details of GEP so that anyone with elementary programming skills will be able to implement it themselves. The book also includes a self-contained introduction to this new exciting field of computational intelligence, including several new algorithms for decision tree induction, data mining, classifier systems, function finding, polynomial induction, times series prediction, evolution of linking functions, automatically defined functions, parameter optimization, logic synthesis, combinatorial optimization, and complete neural network induction. The book also discusses some important and controversial evolutionary topics that might be refreshing to both evolutionary computer scientists and biologists.

This second edition has been substantially revised and extended with five new chapters, including a new chapter describing two new algorithms for inducing decision trees with nominal and numeric/mixed attributes.

Cândida Ferreira thoroughly describes the basic ideas of gene

expression programming (GEP) and numerous modifications to this

powerful new algorithm. This monograph provides all the implementation

details of GEP so that anyone with elementary programming

skills will be able to implement it themselves. The book also includes a

self-contained introduction to this new exciting field of computational

intelligence, including several new algorithms for decision tree

induction, data mining, classifier systems, function finding, polynomial

induction, times series prediction, evolution of linking functions,

automatically defined functions, parameter optimization, logic

synthesis, combinatorial optimization, and complete neural network

induction. The book also discusses some important and controversial

evolutionary topics that might be refreshing to both evolutionary

computer scientists and biologists. This second edition has been

substantially revised and extended with five new chapters, including

a new chapter describing two new algorithms for inducing decision

trees with nominal and numeric/mixed attributes.

Product Details

ISBN-13:
9783642069321
Publisher:
Springer Berlin Heidelberg
Publication date:
10/31/2014
Series:
Studies in Computational Intelligence Series, #21
Edition description:
Softcover reprint of hardcover 2nd ed. 2006
Pages:
480
Product dimensions:
6.14(w) x 9.21(h) x 1.01(d)

Table of Contents

Introduction: The Biological Perspective.- The Entities of Gene Expression Programming.- The Basic Gene Expression Algorithm.- The Basic GEA in Problem Solving.- Numerical Constants and the GEP-RNC Algorithm.- Automatically Defined Functions in Problem Solving.- Polynomial Induction and Time Series Prediction.- Parameter Optimization.- Decision Tree Induction.- Design of Neural Networks.- Combinatorial Optimization.- Evolutionary Studies.

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