Research On The Influence Factors And Prediction Of Coal Price Based On BP Neural Network

Coal is the major energy resources in our country which plays an important supporting role in the rapid development the national economy. However, the coal prices turned down sharply from 2012, enterprise efficiency was further declined, and plenty coal enterprises fell into difficult position, in the future, the slump in coal industry become the new normal phenomenon. Confronting such a serious situation, energy related industries association has issued a number of policies to support the coal industry, but the overall running situation is still not optimistic. What course to follow of the coal price? This problem has aroused great concern in the community, including the industry and politics and so on.Thus, this paper deeply analyzed the formation of coal price in china, profoundly anatomized eight factors, such as costs, production capacity, coal consumption, alternative energy sources, changes in stocks, coal import and export, the international market price of coal and the political and economic policy which influence on the price of coal. Therefore, this paper uses the method of BP artificial neural network, which shows the nonlinear characteristic to research coal prices thesis. The results show that using BP artificial neural network models not only can better reflect the characteristics of nonlinear correlation between variables, but can be used for high accuracy on the coal price prediction. Finally, this paper predicted the quarterly coal price of 2015 and 2016(quarter)by this model, through the time series modeling and forecast of interrelated input(factors)variables. The result provide scientific reference for the establishment of coal enterprise production and management decision-making and government policy system.