Residential Property Price Prediction with FNN Network Model

Abstract

In order to predict the new residential property market price, a Fuzzy Neural Network (FNN) prediction model was proposed. It was used to estimate the appropriate price level for a new property by learning from historical data on the correlations between various factors that influence the prices of properties and the actual selling prices. In particular, an artificial neural network prediction model was developed to compare it accuracy with the fuzzy neural network prediction model. The experimental results show that the fuzzy neural network prediction model has strong function approximation ability and is suitable for residential properties price prediction depending on the quality of the available data.