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Foundations of Rough Sets

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Springer Handbook of Computational Intelligence

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Abstract

The rough set (GlossaryTerm

RS

) approach was proposed by Pawlak as a tool to deal with imperfect knowledge. Over the years the approach has attracted attention of many researchers and practitioners all over the world, who have contributed essentially to its development and applications. This chapter discusses the GlossaryTerm

RS

foundations from rudiments to challenges.

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Abbreviations

AI:

artificial intelligence

AMT:

active media technology

AR:

approximate reasoning

c-granule:

complex granule

CW:

computing with words

GC:

granular computing

IGR:

interactive granular computing

IRGC:

interactive rough granular computing

KDD:

knowledge discovery and data mining

MDL:

minimum description length

PBC:

perception-based computing

RS:

rough set

SQL:

structured query language

VPRSM:

variable precision rough set model

W2T:

wisdom web of things

WisTech:

Wisdom Technology

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Author information

Authors and Affiliations

  1. Faculty of Mathematics, Computer Science and Mechanics, University of Warsaw, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

  2. Knowledge Technology Foundation, Nowogrodzka 31, 00-511, Warsaw, Poland

    Andrzej Jankowski

  3. Springer-Verlag GmbH, Tiergartenstrasse 17, 69121, Heidelberg, Germany

    Roman W. Swiniarski

Authors
  1. Andrzej Skowron
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  2. Andrzej Jankowski
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  3. Roman W. Swiniarski
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Corresponding author

Correspondence to Andrzej Skowron .

Editor information

Editors and Affiliations

  1. Systems Research Inst., Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk

  2. Dep. Electrical and Computer Engineering, University of Alberta, 116 Street 9107, T6J 2V4, Edmonton, Alberta, Canada

    Witold Pedrycz

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Skowron, A., Jankowski, A., Swiniarski, R.W. (2015). Foundations of Rough Sets. In: Kacprzyk, J., Pedrycz, W. (eds) Springer Handbook of Computational Intelligence. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43505-2_21

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  • DOI: https://doi.org/10.1007/978-3-662-43505-2_21

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  • Print ISBN: 978-3-662-43504-5

  • Online ISBN: 978-3-662-43505-2

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