Uncertainty Forecasting in Engineering
This book deals with uncertainty forecasting based on a fuzzy time series approach, including fuzzy random processes and artificial neural networks. A consideration of data and measurement uncertainty enhances forecasting in a wide range of applications, particularly in the fields of engineering, en...
Zapisane w:
| Główni autorzy: | , |
|---|---|
| Format: | Livre numérique |
| Język: | Anglais |
| Wydane: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer
[20..].
Cham : Springer Nature |
| Hasła przedmiotowe: | |
| Dostęp online: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Komentarz: |
L'imprtession du document génère 210 p. Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Uncertainty Forecasting in Engineering, Texte imprimé, 9783540371731 |
| Streszczenie: | This book deals with uncertainty forecasting based on a fuzzy time series approach, including fuzzy random processes and artificial neural networks. A consideration of data and measurement uncertainty enhances forecasting in a wide range of applications, particularly in the fields of engineering, environmental science and civil engineering. Uncertain data are described by means of a new incremental fuzzy representation which permits a complete and accurate estimation of uncertainty. The book is aimed at engineers as well as professionals working in related fields. Descriptive, modeling and forecasting methods pertaining to fuzzy time series are introduced and explained in detail. Emphasis is placed on forecasting with the aid of fuzzy random processes, such as fuzzy ARMA processes and fuzzy white-noise processes, as well as forecasting based on artificial neural networks. All numerical algorithms are comprehensively described and demonstrated by way of practical examples |
|---|---|
| Deskrypcja: | L'imprtession du document génère 210 p. Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Bibliografia: | Bibliogr. Index |
| ISBN: | 9783540371762 |
| Ograniczenie dostępu: | Accès en ligne pour les établissements français bénéficiaires des licences nationales Accès soumis à abonnement pour tout autre établissement Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 |