[Comp-neuro] GEP: Mathematical Modeling by an Artificial Intelligence, 2nd Springer Edition

Candida Ferreira candidaf at gene-expression-programming.com
Tue May 30 12:21:32 CEST 2006


Dear Colleagues,

The second, substantially extended and revised edition of my book is now
available!

Gene Expression Programming: Mathematical Modeling by an Artificial
Intelligence by Candida Ferreira
2nd edition 2006,
478 p. 159 illus., Hardcover
Springer-Verlag, Germany
ISBN: 3-540-32796-7
http://www.gene-expression-programming.com/Books/index.asp


Availability:
Springer-Verlag:
http://www.springer.com/uk/home/engineering?SGWID=3-175-22-139763358-0
Amazon:
http://www.amazon.com/gp/product/3540327967/103-9680295-6879017?v=glance&n=2
83155


About the book:

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.

Book Chapters:

1 Introduction: The Biological Perspective
2 The Entities of Gene Expression Programming
3 The Basic Gene Expression Algorithm
4 The Basic GEA in Problem Solving
5 Numerical Constants and the GEP-RNC Algorithm
6 Automatically Defined Functions in Problem Solving
7 Polynomial Induction and Time Series Prediction
8 Parameter Optimization
9 Decision Tree Induction
10 Design of Neural Networks
11 Combinatorial Optimization
12 Evolutionary Studies


Best regards,
Candida Ferreira
---
Candida Ferreira, Ph.D.
Chief Scientist, Gepsoft
http://www.gene-expression-programming.com/author.asp

GEP: Mathematical Modeling by an Artificial Intelligence
2nd Edition, Springer-Verlag 2006
http://www.gene-expression-programming.com/Books/index.asp

Modeling Software:
http://www.gepsoft.com/



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