Fuzzy Verdict Mechanism to Diagnosis the Yield of Rice

Abstract: This paper expresses the structure of fuzzy expert system by applying the algorithm Fuzzy Verdict Mechanism. The elements of Fuzzy expert system are fuzzification interface, Fuzzy Verdict Mechanism and defuzzification. The knowledge is constructed by using the fuzzification to convert crisp values into fuzzy values. By applying the fuzzy verdict mechanism, diagnosis the yield parameters of rice such as Number of tillers per Hill, Number of grains per panicle and 1000 grain weight, pest and disease incidence, becomes simple for scientist. Fuzzy verdict mechanism uses triangular membership function with mamdani�s inference. Defuzzification method is adopted to convert the fuzzy values into crisp values. The effectiveness of the proposed algorithm was implemented using MATLAB Fuzzy Logic tool box to construct fuzzy expert system for rice.

Keywords: Fuzzy Expert System, Fuzzification, Fuzzy Verdict Mechanism, Defuzzification, rice.