Similarity measure between fuzzy set, fuzzy numbers and fuzzy rules using T Fuzzy Assessment Methodology
نویسندگان
چکیده
This paper expresses the prominent futures of fuzzy expert system by applying the algorithm T Fuzzy Assessment Methodology. Fuzzy expert system consists of the following elements such as fuzzification interface, T Fuzzy Assessment Methodology, and defuzzification. T Fuzzy Assessment Methodology uses the K Ratio to find overlapping between membership function and T Fuzzy similarity measure the similarity between fuzzy set, fuzzy number and fuzzy rule. Similar fuzzy sets are merged to form a common set; a new methodology was framed to identify the similarity between fuzzy rules with fuzzy numbers. Similar fuzzy numbers are merged to reduce the number of rules. The efficiency of the proposed algorithm was implemented using MATLAB Fuzzy Logic tool box to construct fuzzy expert system to diagnosis diabetes.
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