Applications of Soft Computing in Time Series Forecasting - Simulation and Modeling Techniques (Paperback, Softcover reprint of the original 1st ed. 2016)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Studies in Fuzziness and Soft Computing, 330
Release date:	August 2016
First published:	2016
Authors:	Pritpal Singh
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	158
Edition:	Softcover reprint of the original 1st ed. 2016
ISBN-13:	978-3-319-38726-0
Categories:	Books > Computing & IT > Applications of computing > Computer modelling & simulation Books > Science & Mathematics > Mathematics > Applied mathematics > Non-linear science Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-319-38726-X
Barcode:	9783319387260

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