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Time-Series Prediction and Applications

A Machine Intelligence Approach

  • 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

Book

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

Introduction

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.

Keywords

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

Authors and affiliations

  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

  • Book Title Time-Series Prediction and Applications
  • Book Subtitle A Machine Intelligence Approach
  • Authors Amit Konar
    Diptendu Bhattacharya
  • Series Title Intelligent Systems Reference Library
  • Series Abbreviated Title Intel.Syst.Ref.Library
  • DOI https://doi.org/10.1007/978-3-319-54597-4
  • Copyright Information Springer International Publishing Switzerland 2017
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Hardcover ISBN 978-3-319-54596-7
  • Softcover ISBN 978-3-319-85435-9
  • eBook ISBN 978-3-319-54597-4
  • Series ISSN 1868-4394
  • Series E-ISSN 1868-4408
  • Edition Number 1
  • Number of Pages XVIII, 242
  • Number of Illustrations 56 b/w illustrations, 13 illustrations in colour
  • Topics Computational Intelligence
    Artificial Intelligence
    Computational Mathematics and Numerical Analysis
  • Buy this book on publisher's site
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