Prediction of Residential Real Estate Selling Prices in Serbia Using Artifical Neural Networks

Abstract

The increasing housing prices over the past decades have added complexity to the real estate appraisal process. Therefore, it is important to create a proper prediction model which can encapsulate complex dependence of the property price from variable inputs. But, the problem of predicting real estate prices is highly non-linear and depends on many parameters. This research explores the potential of utilizing artificial neural networks (ANNs) to forecast the selling prices of apartments in Belgrade, Serbia, based on various apartment parameters. The findings demonstrate high efficiency of the ANN models in property valuation and, if all the preconditions of property value modelling are met, the ANN technique stands as a reliable valuation approach that could be used by both real estate researchers and professionals.