Hybrid self-organizing modeling systems
The Group Method of Data Handling (GMDH) is a typical inductive modeling method that is built on principles of self-organization for modeling complex systems. However, it is known to often under-perform on non-parametric regression tasks, while time series modeling GMDH exhibits a tendency to find v...
Gardado en:
| Autor Principal: | |
|---|---|
| Outros autores: | , |
| Formato: | Livre numérique |
| Idioma: | Anglais |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edición: | 1st ed. 2009. |
| Series: | Studies in Computational Intelligence
211 |
| Acceso en liña: | 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: | • Hybrid Self-Organizing Modeling Systems, Texte imprimé, 9783642015298 • Hybrid Self-Organizing Modeling Systems, Texte imprimé, 9783642015311 • Hybrid Self-Organizing Modeling Systems, Texte imprimé, 9783642015298 • Hybrid Self-Organizing Modeling Systems, Texte imprimé, 9783642101823 |
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| 100 | 1 | |a Onwubolu, Godfrey C. | |
| 245 | 1 | 0 | |a Hybrid self-organizing modeling systems |c edited by Janusz Kacprzyk, Godfrey C. Onwubolu. |
| 250 | |a 1st ed. 2009. | ||
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Studies in Computational Intelligence |v 211 |x 1860-9503 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a Hybrid Computational Intelligence and GMDH Systems Hybrid Genetic Programming and GMDH System: STROGANOFF Hybrid Genetic Algorithm and GMDH System Hybrid Differential Evolution and GMDH Systems Hybrid Particle Swarm Optimization and GMDH System GAME Hybrid Self-Organizing Modeling System Based on GMDH | |
| 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 The Group Method of Data Handling (GMDH) is a typical inductive modeling method that is built on principles of self-organization for modeling complex systems. However, it is known to often under-perform on non-parametric regression tasks, while time series modeling GMDH exhibits a tendency to find very complex polynomials that cannot model well future, unseen oscillations of the series. In order to alleviate these problems, GMDH has been recently hybridized with some computational intelligence (CI) techniques resulting in more robust and flexible hybrid intelligent systems for solving complex, real-world problems. The central theme of this book is to present in a very clear manner hybrids of some computational intelligence techniques and GMDH approach. The hybrids discussed in the book include GP-GMDH (Genetic Programming-GMDH) algorithm, GA-GMDH (Genetic Algorithm-GMDH) algorithm, DE-GMDH (Differential Evolution-GMDH) algorithm, and PSO-GMDH (Particle Swarm Optimization) algorithm. Also included is the description of the recently introduced GAME (Group Adaptive Models Evolution algorithm. The hybrid character of models and their self-organizing ability give these hybrid self-organizing modeling systems an advantage over standard data mining models. The modeling and data mining solutions of several real-life problems in the areas of engineering, bioinformatics, finance, and economics are presented in the chapters. The book will benefit amongst others, people who are working in the areas of neural networks, machine learning, artificial intelligence, complex system modeling and analysis, and optimization | ||
| 700 | 1 | |a Kacprzyk, Janusz, |d 1947- |4 pbd | |
| 700 | 1 | |a Onwubolu, Godfrey C., |d 19..- |4 pbd | |
| 776 | 0 | |t Hybrid Self-Organizing Modeling Systems |b Texte imprimé |z 9783642015298 | |
| 776 | 0 | |t Hybrid Self-Organizing Modeling Systems |b Texte imprimé |z 9783642015311 | |
| 776 | 0 | |t Hybrid Self-Organizing Modeling Systems |b Texte imprimé |z 9783642015298 | |
| 776 | 0 | |t Hybrid Self-Organizing Modeling Systems |b Texte imprimé |z 9783642101823 | |
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