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...
Salvato in:
| Autore principale: | |
|---|---|
| Natura: | Livre numérique |
| Lingua: | Anglais |
| Pubblicazione: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edizione: | 2nd ed. 2006. |
| Serie: | Studies in Computational Intelligence
21 |
| Accesso online: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) 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 |
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| 100 | 1 | |a Ferreira, Cândida. | |
| 245 | 1 | 0 | |a Gene Expression Programming : |b Mathematical Modeling by an Artificial Intelligence |c by Cândida Ferreira. |
| 250 | |a 2nd ed. 2006. | ||
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Studies in Computational Intelligence |v 21 |x 1860-9503 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a 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 | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a 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 | ||
| 776 | 0 | |t Gene Expression Programming |b Texte imprimé |z 9783540327967 | |
| 776 | 0 | |t Gene Expression Programming |b Texte imprimé |z 9783642069321 | |
| 776 | 0 | |t Gene Expression Programming |b Texte imprimé |z 9783540821380 | |
| 776 | 0 | |t Gene Expression Programming |b Texte imprimé |z 9783540327967 | |
| 776 | 0 | |t Gene Expression Programming |b Texte imprimé |z 9783662601877 | |
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