Evolutionary Optimization of TSK Fuzzy Model to Assist with Real Estate Appraisals

A Takagi-Sugeno-Kang-type fuzzy model to assist with real estate appraisals was developed and optimized using evolutionary algorithms Three approaches were compared in the paper. The first one consisted in learning the rule base, the second one in tuning the membership functions having the rule base optimized and the third one in combining both methods in one process. Six fuzzy models comprising from two to seven input variables referring to the attributes of a property being appraised were evaluated. The evolutionary algorithms were based on Pittsburgh approach with the real coded chromosomes of constant length. The experiments were conducted using training and testing sets prepared on the basis of actual 134 sales transactions made in one of Polish cities and located in a residential section.