Computational intelligence paradigms : innovative applications
System designers are faced with a large set of data which has to be analysed and processed efficiently. Advanced computational intelligence paradigms present tremendous advantages by offering capabilities such as learning, generalisation and robustness. These capabilities help in designing complex s...
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| Auteur principal: | |
|---|---|
| Autres auteurs: | , , , , , , |
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Édition: | 1st ed. 2008. |
| Collection: | Studies in Computational Intelligence
137 |
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Computational Intelligence Paradigms, Innovative Applications, Lakhmi C. Jain, Mika Sato-Ilic, 2008, Berlin, Springer, 1 vol. (VIII-279 p.), Studies in Computational Intelligence, 978-3-540-79473-8 • Computational Intelligence Paradigms, Texte imprimé, 9783642098390 • Computational Intelligence Paradigms, Texte imprimé, 9783540872429 • Computational Intelligence Paradigms, Innovative Applications, Lakhmi C. Jain, Mika Sato-Ilic, 2008, Berlin, Springer, 1 vol. (VIII-279 p.), Studies in Computational Intelligence, 978-3-540-79473-8 |
Table des matières:
- An Introduction to Computational Intelligence Paradigms A Quest for Adaptable and Interpretable Architectures of Computational Intelligence MembershipMap: A Data Transformation for Knowledge Discovery Based on Granulation and Fuzzy Membership Aggregation Advanced Developments and Applications of the Fuzzy ARTMAP Neural Network in Pattern Classification Large Margin Methods for Structured Output Prediction Ensemble MLP Classifier Design Functional Principal Points and Functional Cluster Analysis Clustering with Size Constraints Cluster Validating Techniques in the Presence of Duplicates Fuzzy Blocking Regression Models Support Vector Machines and Features for Environment Perception in Mobile Robotics Linkage Analysis in Genetic Algorithms