Determination of house and apartment prices in the Juiz De Fora region, Minas Gerais, through intelligent algorithms

Abstract

Estate agents value properties, suggesting a price based on their experience and market data, whereas engineers evaluate properties, performing calculations, structural assessments, and property conservation. Nevertheless, specialisedtechnology combining the technical expertise of both professionals can be created to define a valuation range for a specific property. This study presents the application of intelligent classification algorithms, namely, k-nearest neighbour (kNN), artificial neural network multilayer perceptron (MLP), and support vector machine (SVM) algorithms, and teaching-learning-based optimisation (TLBO) as the input selector. The algorithm developed in this study can be used in three neighbourhoods of the city of Juiz de Fora, Minas Gerais state, Brazil, to classify the price of a property in ranges varying from A to F with 75-millisecond classification speed and 82% accuracy. The system can serve to guide and assist estate agents and engineers in their assessment, thus facilitating the work of these professionals by incorporating the techniques of both into its structure since the study was carried out with real properties