Gene Expression Programming

Mathematical Modeling by an Artificial Intelligence

By: Candida Ferreira

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Hardcover | 24 May 2006 | Edition Number 2

At a Glance

Hardcover
504 Pages

Edition Type
Revised

Dimensions(cm)
22.86 x 15.24 x 2.54

Hardcover

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Candida 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.

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You Can Find This Book In

Non-Fiction Science Biology, Life Sciences Life Sciences in General Genetics excluding Medical Mathematics Applied Mathematics Computing & I.T.Computer Science Artificial Intelligence Engineering & Technology Technology in General

Engineering in General

Introduction : the biological perspective	p. 1
The entities of gene expression programming	p. 29
The basic gene expression algorithm	p. 55
The basic GEA in problem solving	p. 121
Numerical constants and the GEP-RNC algorithm	p. 181
Automatically defined functions in problem solving	p. 233
Polynomial induction and time series prediction	p. 275
Parameter optimization	p. 297
Decision tree induction	p. 337
Design of neural networks	p. 381
Combinatorial optimization	p. 405
Evolutionary studies	p. 421
Table of Contents provided by Blackwell. All Rights Reserved.

Gene Expression Programming

Mathematical Modeling by an Artificial Intelligence

At a Glance

Hardcover

Shipping

How to return your order

Defective items

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