A Recent Study on the Rough Set Theory in Multi-Criteria Decision Analysis Problems

被引：3

作者：

Mohamad, Masurah ^{[1
,2
]}

Selamat, Ali ^{[1
,2
]}

Krejcar, Ondrej ^{[3
]}

Kuca, Kamil ^{[3
]}

机构：

[1] Univ Teknol Malaysia, UTM IRDA Digital Media Ctr Excellence, Johor Baharu 81310, Malaysia

[2] Univ Teknol Malaysia, Fac Comp, Johor Baharu 81310, Malaysia

[3] Univ Hradec Kralove, Ctr Basic & Appl Res, Fac Informat & Management, Hradec Kralove 50003, Czech Republic

来源：

COMPUTATIONAL COLLECTIVE INTELLIGENCE (ICCCI 2015), PT II | 2015年 / 9330卷

关键词：

Rough Set Theory; Multi-Criteria Decision Analysis; Multi-Criteria Decision Making; AHP; SELECTION; RULES;

D O I：

10.1007/978-3-319-24306-1_26

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Rough set theory (RST) is one of the data mining tools, which have many capabilities such as to minimize the size of an input data and to produce sets of decision rules from a set of data. RST is also one of the great techniques used in dealing with ambiguity and uncertainty of datasets. It was introduced by Z. Pawlak in 1997 and until now, there are many researchers who really make use of its advantages either to make an enhancement of the RST or to apply in various research areas such as in decision analysis, pattern recognition, machine learning, intelligent systems, inductive reasoning, data preprocessing, knowledge discovery, and expert systems. This paper presents a recent study on the elementary concepts of RST and its implementation in the multi-criteria decision analysis (MCDA) problems.

引用

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页码：265 / 274

页数：10

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