Time Series Analysis, Modeling and Applications

A Computational Intelligence Perspective

  • Witold Pedrycz
  • Shyi-Ming Chen

Part of the Intelligent Systems Reference Library book series (ISRL, volume 47)

Table of contents

  1. Front Matter
    Pages 1-7
  2. Juan Carlos Figueroa-García, Dusko Kalenatic, César Amilcar López
    Pages 31-52
  3. Adam Marszałek, Tadeusz Burczyński
    Pages 77-95
  4. Anna Walaszek-Babiszewska, Katarzyna Rudnik
    Pages 97-118
  5. Yoshiyuki Matsumoto, Junzo Watada
    Pages 177-197
  6. Yi-Chung Cheng, Sheng-Tun Li
    Pages 331-345
  7. Tzu-Yi Pai, Su-Hwa Lin, Pei-Yu Yang, Dyi-Huey Chang, Jui-Ling Kuo
    Pages 369-383
  8. Back Matter
    Pages 0--1

About this book


Temporal and spatiotemporal data form an inherent fabric of the society as we are faced with streams of data coming from numerous sensors, data feeds, recordings associated with numerous areas of application embracing physical and human-generated phenomena (environmental data, financial markets, Internet activities, etc.). A quest for a thorough analysis, interpretation, modeling and prediction of time series comes with an ongoing challenge for developing models that are both accurate and user-friendly (interpretable).

The volume is aimed to exploit the conceptual and algorithmic framework of Computational Intelligence (CI) to form a cohesive and comprehensive environment for building models of time series. The contributions covered in the volume are fully reflective of the wealth of the CI technologies by bringing together ideas, algorithms, and numeric studies, which convincingly demonstrate their relevance, maturity and visible usefulness. It reflects upon the truly remarkable diversity of methodological and algorithmic approaches and case studies.

This volume is aimed at a broad audience of researchers and practitioners engaged in various branches of operations research, management, social sciences, engineering, and economics. Owing to the nature of the material being covered and a way it has been arranged, it establishes a comprehensive and timely picture of the ongoing pursuits in the area and fosters further developments.


Computational Intelligence Evolutionary Optimization Fuzzy Set-based and Granular Models of Time Series Neural Network Models of Time Series

Editors and affiliations

  • Witold Pedrycz
    • 1
  • Shyi-Ming Chen
    • 2
  1. 1., Electrical & Computer EngineeringUniversity of AlbertaEdmontonCanada
  2. 2., Graduate Institute of Educational MeasurNational Taichung University of EducatioTaichungTaiwan R.O.C.

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-642-33438-2
  • Online ISBN 978-3-642-33439-9
  • Series Print ISSN 1868-4394
  • Series Online ISSN 1868-4408
  • Buy this book on publisher's site
Industry Sectors
Materials & Steel
Chemical Manufacturing
Finance, Business & Banking
IT & Software
Consumer Packaged Goods
Energy, Utilities & Environment
Oil, Gas & Geosciences