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Transactions on Computational Collective Intelligence III pp 115–127Cite as

Rule Extraction Based on Rough Fuzzy Sets in Fuzzy Information Systems

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Part of the book series: Lecture Notes in Computer Science ((TCCI,volume 6560))

Abstract

Rough fuzzy sets are an effective mathematical analysis tool to deal with vagueness and uncertainty in the area of machine learning and decision analysis. Fuzzy information systems and fuzzy objective information systems exit in many applications and knowledge reduction in them can’t be implemented by reduction methods in Pawlak information systems. Therefore, this paper provides a model for rule extraction in fuzzy information systems and fuzzy objective information systems.

This approach uses inclusion degree to propose and represent a new and low computation complexity way for knowledge discovery and rough fuzzy concept classifier in fuzzy information systems and fuzzy objective information systems. Also, an illustration example in the construction sector is presented.

This approach is a generalization of rough set model for fuzzy information system. Theory and method of attribute reduction under inclusion degree are suggested in this paper. This approach extends the classical rough set theory from complete information to fuzzy information system.

This proposed model is useful for rule extraction in fuzzy information systems and fuzzy objective information systems to figure our knowledge reduction in fuzzy decision systems.

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Author information

Authors and Affiliations

  1. Department of Information Management, Fooyin University, Taiwan, 151 Chin-Hsueh Rd., Ta-Liao Hsiang Kaohsiung Hsien, 831, Taiwan, ROC

    Ming-Chang Lee

  2. Department of Information Management, Shu-Te University, Taiwan, No. 59, Hengshan Rd., Yanchao Kaohsiung County, Taiwan, ROC

    To Chang

Authors
  1. Ming-Chang Lee
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  2. To Chang
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Editor information

Editors and Affiliations

  1. Department of Information Systems, Wroclaw University of Technology, Poland

    Ngoc Thanh Nguyen

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Lee, MC., Chang, T. (2011). Rule Extraction Based on Rough Fuzzy Sets in Fuzzy Information Systems. In: Nguyen, N.T. (eds) Transactions on Computational Collective Intelligence III. Lecture Notes in Computer Science, vol 6560. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19968-4_6

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  • DOI: https://doi.org/10.1007/978-3-642-19968-4_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19967-7

  • Online ISBN: 978-3-642-19968-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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