Combined Forecast of the Demand of Office Building in Shanghai Based on Artificial Neural Network

Abstract

This paper studies the demand of office building in Shanghai. It defines the demand as the nonlinear function combined with six parameters, including resident population of city, amount of investment on office building construction, the GDP, the rent index of office building, Per capita disposable income and vacancy rate of office buildings. Then, this article uses Logistic Forecasting and Artificial Neural Network to indicate the value of those parameters. Based on the previous precondition and analysis, we forecast the demand of office building in Shanghai by using BP, RBF, ELMAN neural network modes respectively. The result of this paper is demonstrated to be authentic.