R. Babuska, Fuzzy Modeling for Control, Kluwer Academic Publ., Dordrecht, 1998, 288 p. B. Bouchon-Meunier, L. Foulloy, M. Ramdani, Logique Floue Exercices Corriges et Exemples d' Applications, Cepadues Editions. Toulouse, 199B, 200 p. G.Q. Chen, Fuzzy Logic in Data Modeling Semantics, Constraints and Database Design, Kluwer Academic Publ., Boston. 1998, 240 p. K.J. Cios. W. Pedrycz, R.S. Swiniarski. Data Mining Methods for Knowledge Discovery, Kluwer Academic Publ., Dordrecht. 199B. J. Godjevac, Idees Nettes sur la Logique Floue, Presses Polytechniques et Universitaires Romandes. Lausanne, 1997,200 p. E. Hisdal, Logical structures for representation of knowledge and uncertainty, Physica-Verlag, Heidelberg, Germany, 199B. M. Jamshidi, A. Titli, L.A. Zadeh, S. Boverie, Applications of Fuzzy LogiC Towards High Machine Intelligence Quotient Systems, Prentice-Hall, Englewood Cliffs, NJ, 1997,423 p. F. Lootsma, Fuzzy Logic for Planning and Decision Making Applied Optimization 8. Kluwer Academic Publ., Dordrecht, 1998. W. Mielczarski, Fuzzy Logic Techniques in Power Systems, Physica-Verlag, Berlin, 1998, 456 p. J.N. Mordeson, P.S. Nair, Fuzzy Mathematics An Introduction for Engineers and Scientists. Physica-Verlag, Berlin, 1998,270 p. W. Pedrycz, Computational Intelligence An Introduction, CRC Press, Boca Raton, FL, 1997,304 p. M. Reghis, E. Roventa, Classical and Fuzzy Concepts in Mathematical Logic and Applications, CRC Press, Boca Raton, FL, 1998. L. Reznik, Fuzzy Controllers, Newness Press, UK, 1997. Schindler, Fuzzy-Datenanalyse durch kontextbasierte Datenbankanfragen, Deutscher Universitiits Verlag, Leverkusen, Germany, 1998. O. Wolkenhauer, Possibility Theory with Applications to Data Analysis. Research Studies Press, Hertfordshire, UK, 1998, 290 p. Edited volumes

Fuzzy sets and systems

On attribute reduction in concept lattices: Methods based on discernibility matrix are outperformed by basic clarification and reduction

On attribute reduction in concept lattices: The polynomial time discernibility matrix-based method becomes the CR-method

A knowledge reduction approach for linguistic concept formal context

On attribute reduction in concept lattices: Experimental evaluation shows discernibility matrix based methods inefficient

Concept lattice is an effective tool for knowledge discovery and has been applied to many fields successfully. The objects and attributes have clear relations in the classical formal context, but there are a lot of fuzzy information in real-life applications. Therefore, it is important to study the fuzzy formal context. As we know, the fuzzy set and the classical set can be transformed into each other based on the cut set. Thus, it is believed that the cut set can be used in the research of fuzzy concept lattice. In this paper, a preliminary exploration to use the cut set is carried out. In particular, the cut set is employed to construct the discernibility matrix of L-fuzzy formal context and then all the reducts can be obtained via the use of discernibility function. After that, all the attributes are classified into three types by their significances in constructing the L-fuzzy concept lattice. The characteristics of these types of attributes are also analyzed. The obtained results in this paper are beneficial for the research of fuzzy formal context based on the cut set in further.

On the use of cut set for attribute reduction in L-fuzzy concept lattice

A simple discernibility matrix for attribute reduction in formal concept analysis based on granular concepts

Dynamic granularity selection based on local weighted accuracy and local likelihood ratio

This paper introduces a new definition of intuitionistic fuzzy (IF for short) inclusion measure. Five kinds of IF inclusion measure are constructed by means of different operators especially by IF implicator. It is shown that the similarity measure between two IF sets obtained from IF inclusion measure hold properties of normal similarity measure.

Inclusion measure and similarity measure of intuitionistic fuzzy sets

In decision making analysis, ranking decision with anti-noise capability is a very desirable issue. This paper focuses on analysing data in interval-valued information systems. A new approach ranking with weighted standardized cardinality (WSC) and inclusion indicator in interval-valued information systems is proposed. It is a novel generalization of ranking method based on dominance classes. The new approach overcomes the drawback of sensitivity to noise for raking using dominance classes-based method. In this paper, each object with all attribute values is regarded as an interval-valued fuzzy set (IVF-set). By defining WSC with controlling parameters and single interval inclusion indicator, two kinds of inclusion indicators of the IVF-set are constructed. The approach is based on the novel idea of raking with WSC and inclusion indicator rather than dominance classes. Experiments verify that the new approach is noise-resistant.

Bin Xie

Papers

On the use of cut set for attribute reduction in L-fuzzy concept lattice

A simple discernibility matrix for attribute reduction in formal concept analysis based on granular concepts

Dynamic granularity selection based on local weighted accuracy and local likelihood ratio

Inclusion measure and similarity measure of intuitionistic fuzzy sets

A novel approach for ranking in interval-valued information systems