Estimation of Residential Land Price in the Suburban Region of India, A Comparison between Artificial Neural Network and Hedonic Price Model - Sridhar, M. B.; Sathyanathan, R. (International Journal of Intelligent Systems and Applications in Engineering, 2022)
The real estate land price valuation is a global issue, and its importance is not limited to the real estate market but also in the banking sector, insurance sector, and governing bodies for taxation and acquisitions. This paper compares the accuracy of the Hedonic Pricing Model (HPM) and Artificial Neural Network (ANN) model in predicting the residential land price for Chengalpattu district, a suburban region in the southern part of India. Residential land prices and data for the variables affecting land prices were collected and used to develop the HPM and ANN models. Subsequently, both models predicted land prices for newer land parcels, and their accuracy was compared. The performance evaluation indices of root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), R-square and accuracy were calculated for the predicted results of both the models. The HPM predicted the residential land prices with an accuracy of 75 %, whereas the ANN model predicted the prices with an accuracy of 91 %. The study showed that the ANN model is reliable and accurate in residential price prediction for suburban regions.