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Intelligent Systems Reference Library

Time-Series Prediction and Applications

A Machine Intelligence Approach

Authors: Konar, Amit, Bhattacharya, Diptendu

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  • Proposes generic solutions to the prediction of an economic time-series with alternative formulations using machine learning and type-2 fuzzy sets
  • Offers original content and a unique presentation style
  • Includes the source codes of the programs developed in MATLAB to accompany the book
  • Requires a only a high-school understanding of algebra and calculus, and first-year-undergraduate-level programming skills 
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eBook $109.00
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  • ISBN 978-3-319-54597-4
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Softcover $139.99
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  • ISBN 978-3-319-85435-9
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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.

Table of contents (6 chapters)

Table of contents (6 chapters)
  • An Introduction to Time-Series Prediction

    Pages 1-37

    Konar, Amit (et al.)

  • Self-adaptive Interval Type-2 Fuzzy Set Induced Stock Index Prediction

    Pages 39-103

    Konar, Amit (et al.)

  • Handling Main and Secondary Factors in the Antecedent for Type-2 Fuzzy Stock Prediction

    Pages 105-132

    Konar, Amit (et al.)

  • Learning Structures in an Economic Time-Series for Forecasting Applications

    Pages 133-188

    Konar, Amit (et al.)

  • Grouping of First-Order Transition Rules for Time-Series Prediction by Fuzzy-Induced Neural Regression

    Pages 189-233

    Konar, Amit (et al.)

Buy this book

eBook $109.00
price for USA in USD
  • ISBN 978-3-319-54597-4
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $179.99
price for USA in USD
  • ISBN 978-3-319-54596-7
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually ready to be dispatched within 3 to 5 business days.
Softcover $139.99
price for USA in USD
  • ISBN 978-3-319-85435-9
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually ready to be dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Time-Series Prediction and Applications
Book Subtitle
A Machine Intelligence Approach
Authors
Series Title
Intelligent Systems Reference Library
Series Volume
127
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-54597-4
DOI
10.1007/978-3-319-54597-4
Hardcover ISBN
978-3-319-54596-7
Softcover ISBN
978-3-319-85435-9
Series ISSN
1868-4394
Edition Number
1
Number of Pages
XVIII, 242
Number of Illustrations
56 b/w illustrations, 13 illustrations in colour
Topics

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