Applications of Soft Computing in Time Series Forecasting

Simulation and Modeling Techniques

  • Pritpal Singh

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 330)

Table of contents

  1. Front Matter
    Pages i-xxi
  2. Pritpal Singh
    Pages 1-9
  3. Pritpal Singh
    Pages 127-148
  4. Pritpal Singh
    Pages 149-153
  5. Back Matter
    Pages 155-158

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.



Fuzzy Time Series Modeling Type 2 Fuzzy Time Series Model Hybrid Neuro-fuzzy Models FTS-PSO Model M-Factors Time Series Forecasting ANN Applications in Forecasting Monsoon Rainfall Prediction ISMR Prediction

Authors and affiliations

  • Pritpal Singh
    • 1
  1. 1.Dept. of Computer Science & EngineeringThapar University Dept. of Computer Science & EngineeringPatialaIndia

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-319-26292-5
  • Online ISBN 978-3-319-26293-2
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • Buy this book on publisher's site
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