Rough Sets: Selected Methods and Applications in Management and Engineering

  • Georg Peters
  • Pawan Lingras
  • Dominik Ślęzak
  • Yiyu Yao

Part of the Advanced Information and Knowledge Processing book series (AI&KP)

Table of contents

  1. Front Matter
    Pages I-X
  2. Foundations of Rough Sets

    1. Front Matter
      Pages 1-1
    2. Yiyu Yao, Dominik Ślęzak
      Pages 3-20
  3. Methods and Applications in Data Analysis

    1. Front Matter
      Pages 21-21
    2. Pawan Lingras, Georg Peters
      Pages 23-37
    3. Fernando Crespo, Georg Peters, Richard Weber
      Pages 39-50
  4. Methods and Applications in Decision Support

    1. Front Matter
      Pages 77-77
    2. Sebastian Widz, Dominik Ślęzak
      Pages 95-112
  5. Methods and Applications in Management

    1. Front Matter
      Pages 113-113
    2. Pawan Lingras, Cory Butz, Parag Bhalchandra
      Pages 115-127
    3. Georg Peters, Roger Tagg
      Pages 143-160
  6. Methods and Applications in Engineering

    1. Front Matter
      Pages 161-161
    2. Marek Sikora, Beata Sikora
      Pages 163-179
    3. Sheela Ramanna, James F. Peters
      Pages 181-205
  7. Back Matter
    Pages 207-214

About this book

Introduction

Rough Set Theory was introduced in the early 1980's. In the last quarter century it has become an important part of soft computing and has proved its relevance in many real-world applications.

Initially most articles on Rough Sets were centered on theory, currently though the focus of the research has shifted to practical usage of mathematical advances. With this in mind this book is written for researchers at universities wanting to use Rough Sets to solve real-world problems and needing guidance on how best to describe their ideas in ways not only understandable to industry readers, but also for managers looking for methods to improve their businesses, and researchers in industrial laboratories and think-tanks investigating new methods to enhance the efficiency of their solutions.

Rough Sets: Selected Methods and Applications in Management and Engineering is unique in its focus on use cases backed by sound theory in contrast to the presentation of a theory applied to a problem. A diverse range of applications, including coverage of methods in data analysis, decision support as well as management and engineering, demonstrates the great potential of Rough Sets in almost any domain.

Keywords

Artificial Intelligence Data Mining Rough Set Theory Rough Sets

Editors and affiliations

  • Georg Peters
    • 1
  • Pawan Lingras
    • 2
  • Dominik Ślęzak
    • 3
  • Yiyu Yao
    • 4
  1. 1.Munich University of Applied SciencesMunichGermany
  2. 2.Dpt. of Mathematics and Computer ScienceSt. Mary's UniversityHalifaxCanada
  3. 3.University of WarsawWarsawPoland
  4. 4.Department of Computer ScienceUniversity of ReginaReginaCanada

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-2760-4
  • Copyright Information Springer-Verlag London Limited 2012
  • Publisher Name Springer, London
  • eBook Packages Computer Science
  • Print ISBN 978-1-4471-2759-8
  • Online ISBN 978-1-4471-2760-4
  • Series Print ISSN 1610-3947
  • About this book
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