Time-Series Prediction and Applications

A Machine Intelligence Approach

  • Amit Konar
  • Diptendu Bhattacharya

Part of the Intelligent Systems Reference Library book series (ISRL, volume 127)

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Amit Konar, Diptendu Bhattacharya
    Pages 1-37
  3. Amit Konar, Diptendu Bhattacharya
    Pages 39-103
  4. Amit Konar, Diptendu Bhattacharya
    Pages 133-188
  5. Amit Konar, Diptendu Bhattacharya
    Pages 235-236
  6. Back Matter
    Pages 237-242

About this book


This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series

Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at the end of each chapter to the readers’ ability and understanding of the topics covered.


Intelligent Systems Computational Intelligence Time Series Prediction Machine Learning Type-2 Fuzzy Sets

Authors and affiliations

  • Amit Konar
    • 1
  • Diptendu Bhattacharya
    • 2
  1. 1.Dept of Electronics & Tele-CommJadavpur University Dept of Electronics & Tele-CommKolkataIndia
  2. 2.Dept. of Computer Science and EngineerinNIT Agartala Dept. of Computer Science and EngineerinTripuraIndia

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2017
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-319-54596-7
  • Online ISBN 978-3-319-54597-4
  • Series Print ISSN 1868-4394
  • Series Online ISSN 1868-4408
  • Buy this book on publisher's site
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