Solving P - Norm Intuitionistic Fuzzy Programming Problem

In this paper, notion of p - norm generalized trapezoidal intuitionistic fuzzy numbers is introduced. A new ranking method is introduced for p - norm generalized trapezoidal intuitionistic fuzzy numbers. Also we consider linear programming problem in intuitionistic fuzzy environment. In this problem, all the coefficients and variables are represented by p - norm generalized trapezoidal intuitionistic fuzzy numbers. To overcome the limitations of the existing methods, a new method is proposed to compute the intuitionistic fuzzy optimal solution for intuitionistic fuzzy linear programming problem. An illustrative numerical example is solved to demonstrate the efficiency of the proposed approach.Comment: some erro

Soft ranking in clustering

Due to the diffusion of large-dimensional data sets (e.g., in DNA microarray or document organization and retrieval applications), there is a growing interest in clustering methods based on a proximity matrix. These have the advantage of being based on a data structure whose size only depends on cardinality, not dimensionality. In this paper, we propose a clustering technique based on fuzzy ranks. The use of ranks helps to overcome several issues of large-dimensional data sets, whereas the fuzzy formulation is useful in encoding the information contained in the smallest entries of the proximity matrix. Comparative experiments are presented, using several standard hierarchical clustering techniques as a reference