Evolving Fuzzy Systems Methodologies, Advanced Concepts and Applications
In today s real-world applications, there is an increasing demand of integrating new information and knowledge on-demand into model building processes to account for changing system dynamics, new operating conditions, varying human behaviors or environmental influences. Evolving fuzzy systems (EFS)...
Enregistré dans:
| Hovedforfatter: | |
|---|---|
| Format: | Livre numérique |
| Sprog: | Anglais |
| Udgivet: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Serier: | Studies in Fuzziness and Soft Computing
266 |
| Online adgang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
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Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Evolving fuzzy system, methodologies, advanced concepts and applications, Edwin Lughofer, Berlin, Springer-Verlag, 2011, 1 vol. (XXIV-454 p., Studies in Fuzziness and Soft Computing, 978-3-642-18086-6 |
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| 100 | 1 | |a Lughofer, Edwin. | |
| 245 | 1 | 0 | |a Evolving Fuzzy Systems Methodologies, Advanced Concepts and Applications |c by Edwin Lughofer. |
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Studies in Fuzziness and Soft Computing |v 266 |x 1434-9922 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a I. Introduction Part I - Basic Methodologies II. Basic Algorithms for EFS III. EFS Approaches for Regression and Classification Part II - Advanced Concepts IV. Towards Robust and Process-Save EFS V. On Improving Performance and Increasing Useability of EFS VI. Interpretability Issues in EFS Part III Applications VII. Online System Identification and Prediction VIII. On-Line Fault and Anomaly Detection IX. Visual Inspection Systems X. Further (Potential) Application Fields Epilog - Achievements, Open Problems and New Challenges in EFS | |
| 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 In today s real-world applications, there is an increasing demand of integrating new information and knowledge on-demand into model building processes to account for changing system dynamics, new operating conditions, varying human behaviors or environmental influences. Evolving fuzzy systems (EFS) are a powerful tool to cope with this requirement, as they are able to automatically adapt parameters, expand their structure and extend their memory on-the-fly, allowing on-line/real-time modeling. This book comprises several evolving fuzzy systems approaches which have emerged during the last decade and highlights the most important incremental learning methods used. The second part is dedicated to advanced concepts for increasing performance, robustness, process-safety and reliability, for enhancing user-friendliness and enlarging the field of applicability of EFS and for improving the interpretability and understandability of the evolved models. The third part underlines the usefulness and necessity of evolving fuzzy systems in several online real-world application scenarios, provides an outline of potential future applications and raises open problems and new challenges for the next generation evolving systems, including human-inspired evolving machines. The book includes basic principles, concepts, algorithms and theoretic results underlined by illustrations. It is dedicated to researchers from the field of fuzzy systems, machine learning, data mining and system identification as well as engineers and technicians who apply data-driven modeling techniques in real-world systems | ||
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