Forecasting the Land Price Using Statistical and Neural Network Software

This paper focuses on the modelling and forecasting of land price in Chennai Metropolitan Area (CMA) in the state of Tamilnadu, India using multiple regression and neural network techniques. Thirteen locations spread over CMA are selected at random as study areas. The monthly average values of the selected factors from the year 1997 to 2011 are considered to develop the models. Both multiple regression and neural network models are validated with the market price in the year 2012 and 2013. After validation the models are used to forecast the land price in CMA for the years 2014 and 2015. Both the models are found to be well fit for the trend of land price; however the model using neural network shows better accuracy. A careful examination of the results of forecasting bring to lime light the surge in growth of land prices in the southern and western parts of CMA.