Authors:
- Provides the readers with the necessary theoretical background and practical tools for designing time series forecasting models using a combination of soft computing techniques
- Presents improved methods for fuzzy time series modeling
- Includes a detailed analysis of the reported models, from their formulation, to the empirical tests, including their performance measures
- Shows a model implementation for summer monsoon rainfall prediction
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 330)
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Table of contents (8 chapters)
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Front Matter
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Back Matter
About this book
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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Authors and Affiliations
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Dept. of Computer Science & Engineering, Thapar University Dept. of Computer Science & Engineering, Patiala, India
Pritpal Singh
Bibliographic Information
Book Title: Applications of Soft Computing in Time Series Forecasting
Book Subtitle: Simulation and Modeling Techniques
Authors: Pritpal Singh
Series Title: Studies in Fuzziness and Soft Computing
DOI: https://doi.org/10.1007/978-3-319-26293-2
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Hardcover ISBN: 978-3-319-26292-5Published: 30 November 2015
Softcover ISBN: 978-3-319-38726-0Published: 23 August 2016
eBook ISBN: 978-3-319-26293-2Published: 22 November 2015
Series ISSN: 1434-9922
Series E-ISSN: 1860-0808
Edition Number: 1
Number of Pages: XXI, 158
Number of Illustrations: 10 b/w illustrations, 14 illustrations in colour
Topics: Computational Intelligence, Applications of Nonlinear Dynamics and Chaos Theory, Simulation and Modeling, Artificial Intelligence