Attribute Reduction in Intuitionistic Fuzzy Concept Lattices | Zendy

Jinzhong Pang | Zendy; Xiaoyan Zhang | Zendy; Weihua Xu | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Attribute Reduction in Intuitionistic Fuzzy Concept Lattices

Author(s) -

Jinzhong Pang,

Xiaoyan Zhang,

Weihua Xu

Publication year - 2013

Publication title -

abstract and applied analysis

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.228

H-Index - 56

eISSN - 1687-0409

pISSN - 1085-3375

DOI - 10.1155/2013/271398

Subject(s) - mathematics , lattice (music) , formal concept analysis , fuzzy logic , knowledge extraction , rough set , lattice reduction , algebra over a field , theoretical computer science , data mining , artificial intelligence , computer science , pure mathematics , algorithm , physics , acoustics , beamforming , statistics , mimo

As an effective tool for knowledge discovery, concept lattice has been successfully applied to various fields. And one of the key problems of knowledge discovery is attribute reduction. In order to understand the problems better, the attribute reduction is necessary to perfect the theory as well as expand application of concept lattice. This paper introduces the intuitionistic fuzzy theory into the concept lattice theory and proposes a kind of intuitionistic fuzzy concept lattice. Then, an approach to attribute reduction based on the discernibility matrix is proposed and investigated, which makes the discovery of implicit knowledge easier and the representation simpler in data; furthermore, the theory of concept lattice is perfected. The theory of intuitionistic fuzzy concept lattice is useful and meaningful in view of the complexity and fuzziness of information in real world, and the potential value of dealing with information is expected in the future

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research