Housing price prediction using neural networks
The forecast of Singapore condominium prices is important for potential buyers to make informed decisions. This paper applies two algorithms to predict Singapore housing market and to compares the predictive performance of artificial neural network (ANN) model, i.e., the multilayer perceptron, with autoregressive integrated moving average (ARIMA) model. The more superior model is used to predict the future condominium price index (CPI). The lower mean square error (MSE) of the ANN models showed the superiority of ANN over other predictive tools.