Abstract
Takagi-Sugeno-Kang fuzzy model to assist with real estate appraisals is described and optimized using evolutionary algorithms. Two approaches were compared in the paper. The first one consisted in learning the rule base and the second one in combining learning the rule base and tuning the membership functions in one process. Moreover two model variants with three and five triangular and trapezoidal membership functions describing each input variable were tested. Several TSK fuzzy models comprising different number of input variables were evaluated using the MATLAB. The evolutionary algorithms were based on Pittsburgh approach with the real coded chromosomes of constant length comprising whole rule base or both the rule base and all parameters of all membership functions. The experiments were conducted using training and testing sets prepared on the basis of actual 150 sales transactions made in one of Polish cities and located in a residential section. The results obtained were not decisive and further research in this area is needed.
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