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Applications of Soft Computing in Time Series Forecasting: Simulation and Modeling Techniques

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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.

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Detail Information

Series Title

Studies in Fuzziness and Soft Computing

Call Number

006.3 SIN a

Publisher

Cham, Switzerland : Springer Cham., 2015

Collation

XXI, 158

Language

English

ISBN/ISSN

978-3-319-26293-2

Classification

006.3

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

Ed. 1

Subject(s)

Artificial Intelligence
Computational Intelligence

Specific Detail Info

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Statement of Responsibility

Pritpal Singh

Other Information

Cataloger

umi

Source

https://link.springer.com/content/pdf/10.1007/978-3-319-26293-2.pdf?pdf=button

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