Applications of Soft Computing in Time Series Forecasting | Simulation and Modeling Techniques
Language: English
Published by Springer, 2016
Series: Book 103 of 183 - Studies in Fuzziness and Soft Computing
- Softcover
- New
Condition: New
US$ 110.01
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Applications of Soft Computing in Time Series Forecasting | Simulation and Modeling Techniques | Pritpal Singh | Taschenbuch | Studies in Fuzziness and Soft Computing | xxi | Englisch | 2016 | Springer | EAN 9783319387260 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Seller Inventory # 109581195
- Title
- Applications of Soft Computing in Time Series Forecasting | Simulation and Modeling Techniques
- Author
- Pritpal Singh
- Publisher
- Springer
- Publication year
- 2016
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 331938726X
- ISBN 13
- 9783319387260
- Item weight
- 283 grams
- Dimensions
- 235 x 155 x 11 mm
- Series
- Book 103 of 183: Studies in Fuzziness and Soft Computing
- Seller catalogs
- Bücher
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.
"Synopsis" may belong to another edition of this title.
From the Back Cover
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.
"About the title" may belong to another edition of this title.
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