Using PLSRGM (0, N) Method to Predict China's Transportation Sector Energy Demand

Abstract

Because the transportation sector consumes more and more energy, it is important to predict future transport energy demand for sustainable transport. In this paper, a new method PLSRGM (0, N) is proposed by integrating PLSR (partial least square regression) into GM (0, N). Then TEDM (transport energy demand model) based on PLSRGM(0,N) will be activated using GDP, population, urban per capita disposal, rural per capita net income, passenger-kilometers and freight ton-kilometers with historical energy data available from 1997 to 2006. The results of posteriori checks show that the model is more reliable and has higher forecasting accuracy. The projections are made with two scenarios until 2030. It is expected that this paper will provide an effective tool to develop energy model that will greatly assist policy-makers.