Fuzzy System Model to Assist with Real Estate Appraisals

Abstract

Real estate appraisal requires expert knowledge and should be performed by licensed professionals. Prior to the evaluation the appraiser must conduct a thorough study of the appraised property i.e. a land parcel and/or a building. Despite the fact that he sometimes uses the expertise of the surveyor, the builder, the economist or the mortgage lender, his estimations are usually subjective and are based on his experience and intuition. The primary goal of the paper is to present the concept of a fuzzy rule-based system to assist with real estate appraisals. The input variables of the system comprise seven attributes of a property and as the output the system proposes the property’s value. For the appraisal area, so called representative property is determined and in fact the deviations of property attribute values from the representative ones are the input into the fuzzy system. The proportion of the representative property price to the value of the property being assessed is produced as the output of the system. The experts have built the Mamdani model of the system, however they have not been able to construct the rule base. Therefore an evolutionary algorithm has been employed to generate the rule base. The Pittsburgh approach has been applied. The learning process has been conducted using training and testing sets prepared on the basis of 150 sales transactions from one city.