Study On Coal Logistics Demand Prediction Based On The Grey Neural Network Model

As the first energy of China’s long-term dependence on, coal plays a important position in the national energy development strategy. Effective and scientific prediction of coal demand will speed the scientific development of the coal industry and also be helpful for adjusting the energy structure of our country. This provides the necessary decision data for coal logistics development planning, and logistics infrastructure construction.On the base exposition of the logistics demand forecast, a particular industry predictions and coal logistics related analysis theory, combine with the content of coal logistics demand analysis, this paper determined that mainly from the point of coal consumption, railway, waterway, and highway coal traffic volume, and the amount of coal circulation processing to forecast coal logistics demand scale. This paper established the coal demand forecasting index system. Then, make use of grey prediction model, BP neural network model, and grey neural network model to forecast coal demand. Comparison of three model predictions, the forecast result of combined model is better than a single prediction model. Then using gray neural network combination model forecast for2011-2016years of coal consumption, according to the prediction result of coal consumption, forecast the amount of railway, waterway, highway coal traffic volume and coal circulation processing.Scientific prediction the demand of coal logistics, can effectively avoid blind investment to coal logistics infrastructure, so that the coal logistics supply and demand to match each other. According to the forecast results, put forward the policy recommendations about development of coal logistics, in order to achieve the sustainable development of coal energy.