An Overview of Quotient Space Theory
Xu Wang, Shi Fei Ding
Abstract
Xu Wang, Shi Fei Ding
Abstract
Granular computing (GrC) is another solving method of artificial intelligence problems after neural network, fuzzy set theory, genetic algorithm, evolutionary algorithm and so on. GrC involves all the theories, methodologies and techniques of granularity, providing a powerful tool for the solution of complex problems, massive data mining, and fuzzy information processing. Quotient space theory is a representative model of granular computing. In this paper, first the current situation and the development prospects of quotient space theory are introduced, then the basic theory of quotient space granular computing are presented and the stratified and synthesis principle of granularity are summarized. Finally we discuss some important issues such as the application and promotion of quotient space
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Granular computing (GrC) is another solving method of artificial intelligence problems after neural network, fuzzy set theory, genetic algorithm, evolutionary algorithm and so on. GrC involves all the theories, methodologies and techniques of granularity, providing a powerful tool for the solution of complex problems, massive data mining, and fuzzy information processing. Quotient space theory is a representative model of granular computing. In this paper, first the current situation and the development prospects of quotient space theory are introduced, then the basic theory of quotient space granular computing are presented and the stratified and synthesis principle of granularity are summarized. Finally we discuss some important issues such as the application and promotion of quotient space
Key concepts: Granular computing, Quotient space (topology), Granularity, Rough set, Quotient, Computational intelligence, Space (punctuation), Theoretical computer science