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Applications of Soft Computing in Time Series Forecasting Simulation and Modeling Techniques /
This book reports on an in-depth study of fuzzy time series (FTS) modeling. It reviews and summarizes previous research work in FTS modeling and also provides a brief introduction to other soft-computing techniques, such as artificial neural networks (ANNs), rough sets (RS) and evolutionary computin...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2016.
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| Edición: | 1st ed. 2016. |
| Colección: | Studies in Fuzziness and Soft Computing,
330 |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 001 | 978-3-319-26293-2 | ||
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| 100 | 1 | |a Singh, Pritpal. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Applications of Soft Computing in Time Series Forecasting |h [electronic resource] : |b Simulation and Modeling Techniques / |c by Pritpal Singh. |
| 250 | |a 1st ed. 2016. | ||
| 264 | 1 | |a Cham : |b Springer International Publishing : |b Imprint: Springer, |c 2016. | |
| 300 | |a XXI, 158 p. 24 illus., 14 illus. in color. |b online resource. | ||
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| 490 | 1 | |a Studies in Fuzziness and Soft Computing, |x 1860-0808 ; |v 330 | |
| 520 | |a This book reports on an in-depth study of fuzzy time series (FTS) modeling. It reviews and summarizes previous research work in FTS modeling and also provides a brief introduction to other soft-computing techniques, such as artificial neural networks (ANNs), rough sets (RS) and evolutionary computing (EC), focusing on how these techniques can be integrated into different phases of the FTS modeling approach. In particular, the book describes novel methods resulting from the hybridization of FTS modeling approaches with neural networks and particle swarm optimization. It also demonstrates how a new ANN-based model can be successfully applied in the context of predicting Indian summer monsoon rainfall. Thanks to its easy-to-read style and the clear explanations of the models, the book can be used as a concise yet comprehensive reference guide to fuzzy time series modeling, and will be valuable not only for graduate students, but also for researchers and professionals working for academic, business and government organizations. . | ||
| 650 | 0 | |a Computational intelligence. | |
| 650 | 0 | |a Nonlinear Optics. | |
| 650 | 0 | |a Computer simulation. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 1 | 4 | |a Computational Intelligence. |
| 650 | 2 | 4 | |a Nonlinear Optics. |
| 650 | 2 | 4 | |a Computer Modelling. |
| 650 | 2 | 4 | |a Artificial Intelligence. |
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| 773 | 0 | |t Springer Nature eBook | |
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| 776 | 0 | 8 | |i Printed edition: |z 9783319387260 |
| 830 | 0 | |a Studies in Fuzziness and Soft Computing, |x 1860-0808 ; |v 330 | |
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