BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (Studies in Computational Intelligence, 21)

Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (Studies in Computational Intelligence, 21)

Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence
Stock photo: cover may vary

Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (Studies in Computational Intelligence, 21) Hardback - 2006

by Ferreira, Candida

Add to wish list
  • New
  • Hardback
New

Description

Springer, 2006-05-24. 2nd. hardcover. New. 6.00x1.00x9.00. Buy with confidence. Excellent Customer Service & Return policy.
Ask the seller a question Add to wish list
A$237.77
Free Delivery within USA
Standard delivery: 5 to 10 days
More delivery options
Dropship order
Ships from Ergodebooks (Texas, United States)

Details

About Ergodebooks Texas, United States

Biblio member since 2005

Our goal is to provide best customer service and good condition books for the lowest possible price. We are always honest about condition of book. We list book only by ISBN # and hence exact book is guaranteed.

Terms of Sale:

We have 30 day return policy.

Browse books from Ergodebooks

Reader reviews for Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (Studies in Computational Intelligence, 21)

From the publisher

Cndida 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.

From the rear cover

Cndida 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 fivenew chapters, including a new chapter describing two new algorithms for inducing decision trees with nominal and numeric/mixed attributes.

Cndida 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. Thebook 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.

tracking-