Designing and developing Intuitionistic Fuzzy Logic Toolbox in MATLAB: Membership and non-membership functions gallery

Abstract

The authors have designed and developed algorithms for pattern recognition and clustering techniques using intuitionistic fuzzy (IF) sets, IF operators, IF logic (IFL) – shortest path in networks using IF graphs and IF hypergraphs – video processing using temporal IF sets, RGB image representation through IF index matrices, and molecular structure representation through IF directed hypergraphs. The three major steps involved in the above-said modeling processes via IFSs are (i) intuitionistic fuzzification, (ii) modification of membership and non- membership values (using IF logic/operators/rules/relations) and (iii) intuitionistic defuzzification. While developing these algorithms, parameter tuning was one of the major limitations, and hence specific values were assigned to complete the running process. To overcome this, it is necessary to introduce a toolbox in MATLAB so that the users can select the appropriate tools and parameterize them. Hence, in the long process of contributing a full-pledged intuitionistic fuzzy logic toolbox, namely IFL Toolbox in MATLAB, the membership and non-membership functions gallery has been developed initially, as one of the modules which is the foundation for any IFL control system. This module contains functions, codes, examples and figures/graphs, which will be available on the MATLAB creation page. The proposed module is compared with the existing fuzzy logic toolbox in MATLAB and verified.