Rough set theory and its application in the intelligent systems

Author

Pan, Wei ; Yi, Jinhui ; San, Ye

Author_Institution

Harbin Inst. of Technol., Harbin

fYear

2008

fDate

25-27 June 2008

Firstpage

3706

Lastpage

3711

Abstract

The rough set theory is a new mathematical tool to study vague and uncertain information, and is widely used in intelligent systems. In this paper, the basic ideas of rough set theory are introduced, and the notion of up and low approximation sets, attribute reduction, core and some extensions of rough set theory are also presented. Then the application of rough set theory in intelligent systems. The combination of rough sets with fuzzy sets, neural network and genetic algorithms is mainly reviewed, which gives new ideas and methods to solve the hard problems in intelligent control.

Keywords

fuzzy set theory; genetic algorithms; neurocontrollers; rough set theory; approximation set; attribute reduction; fuzzy set; genetic algorithm; intelligent control; intelligent system; mathematical tool; neural network; rough set theory; Automation; Computational and artificial intelligence; Educational institutions; Fuzzy sets; Genetic algorithms; Intelligent control; Intelligent systems; Neural networks; Rough sets; Set theory; attribute reduction; fuzzy set; genetic algorithms; intelligent system; neural network; rough set;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on

Conference_Location

Chongqing

Print_ISBN

978-1-4244-2113-8

Electronic_ISBN

978-1-4244-2114-5

Type

conf

DOI

10.1109/WCICA.2008.4593519

Filename

4593519