Fuzzy decision support system with rough set based rules generation method

Grzegorz Drwal; Marek Sikora

doi:10.1007/978-3-540-25929-9_92

Fuzzy decision support system with rough set based rules generation method

Grzegorz Drwal
, Marek Sikora

Department of Computer Networks and Systems (RAU/RAU9)

Silesian University of Technology

Research output: Contribution to journal › Conference article › peer-review

6 Citations (Scopus)

Abstract

This paper presents system which tries to combine the advantages of rough sets methods and fuzzy sets methods to get better classification. The fuzzy sets theory supports approximate reasoning and the rough sets theory is responsible for data analyzing and process of automatic fuzzy rules generation. The system was designed as a typical knowledge based system consisting of four main parts: rule extractor, knowledge base, inference engine, user interface and occurs to be useful tool in various decision problems and fuzzy control.

Original language	English
Pages (from-to)	727-732
Number of pages	6
Journal	Lecture Notes in Computer Science
Volume	3066
DOIs	https://doi.org/10.1007/978-3-540-25929-9_92
Publication status	Published - 2004
Event	4th International Conference, RSCTC 2004 - Uppsala, Sweden Duration: 1 Jun 2004 → 5 Jun 2004

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

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10.1007/978-3-540-25929-9_92

Cite this

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title = "Fuzzy decision support system with rough set based rules generation method",

abstract = "This paper presents system which tries to combine the advantages of rough sets methods and fuzzy sets methods to get better classification. The fuzzy sets theory supports approximate reasoning and the rough sets theory is responsible for data analyzing and process of automatic fuzzy rules generation. The system was designed as a typical knowledge based system consisting of four main parts: rule extractor, knowledge base, inference engine, user interface and occurs to be useful tool in various decision problems and fuzzy control.",

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AU - Sikora, Marek

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AB - This paper presents system which tries to combine the advantages of rough sets methods and fuzzy sets methods to get better classification. The fuzzy sets theory supports approximate reasoning and the rough sets theory is responsible for data analyzing and process of automatic fuzzy rules generation. The system was designed as a typical knowledge based system consisting of four main parts: rule extractor, knowledge base, inference engine, user interface and occurs to be useful tool in various decision problems and fuzzy control.

UR - https://www.scopus.com/pages/publications/9444254124

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DO - 10.1007/978-3-540-25929-9_92

M3 - Conference article

AN - SCOPUS:9444254124

SN - 0302-9743

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JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

T2 - 4th International Conference, RSCTC 2004

Y2 - 1 June 2004 through 5 June 2004

ER -

Fuzzy decision support system with rough set based rules generation method

Abstract

ASJC Scopus subject areas

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