Gene Expression Programming : Mathematical Modeling by an Artificial Intelligence

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 themselve...

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Détails bibliographiques
Auteur principal: Ferreira, Cândida
Format: Livre numérique
Langue:Anglais
Publié: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
Édition:2nd ed. 2006.
Collection:Studies in Computational Intelligence 21
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Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Gene Expression Programming, Texte imprimé, 9783540327967
• Gene Expression Programming, Texte imprimé, 9783642069321
• Gene Expression Programming, Texte imprimé, 9783540821380
• Gene Expression Programming, Texte imprimé, 9783540327967
• Gene Expression Programming, Texte imprimé, 9783662601877
Description
Résumé: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
Description:Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
ISBN:9783540328490
ISSN:1860-9503
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