Research On The Demand Prediction Of Coal Logistics Based On The Grey Neural Network In Shanxi Province

As the main force in China’s energy consumption structure, coal is in the extremely important position in the national energy development strategy. The distribution of China’s coal resource is affected by such factors as the resources endowment, and mainly concentrates in the central and western regions, the dislocation phenomenon between resource distribution and consumption configuration made China’s coal resources present the pattern of" west coal send to east, north coal send to south". Therefore, the coal logistics has become an important lever to adjust the balance of supply and demand of China’s coal resources. Strengthening the research on demand prediction of China’s coal logistics, and ensuring the efficient operation of coal logistics system to adapt to the needs of the development of regional economy, plays an important role in avoiding economic development bottleneck caused by the deficiency of coal logistics supply capacity, or excessive investment caused by the surplus of coal logistics supply capacity, and the phenomenon redundant construction such as infrastructure.Taking China coal logistics demand as the research object, and taking the prediction system and the prediction method as the main research problems, the paper adopts the method of data collection and qualitative analysis, and uses the macro and micro analysis tool to first make a systematic analysis of factors affecting the forecasting of China’s coal logistics demand from the perspective of the production, supply and sales of coal resources, and construct the comprehensive index system of demand forecasting of China’s coal logistics. Then, reviewing and analyzing the general method and their characteristics of logistics demand forecasting, combining with the characteristics of China’s coal logistics demand forecasting and the advantage of grey neural network forecasting method, choose the combination forecast method of grey system and neural network to forecast the coal logistics demand, and builds the grey neural network forecasting model of the coal logistics demand. Finally, combining with the economic development of Shanxi Province and the characteristics of the coal logistics development, based on the grey neural network forecasting model of the coal logistics demand, it sets the index system of coal logistics demand forecasting in Shanxi Province, makes a forecast and analysis of coal logistics demand in Shanxi Province, and puts forward suggestions for Shanxi coal logistics development from the macro, meso and micro three levels.The difficult points and possible innovations of the article:①it combines logistics demand and the real industry, puts forward the research angle of view of the coal logistics demand forecast, and designs the comprehensive index system of the coal logistics demand forecasting, so as to provide new train of thought and research direction for the logistics demand forecasting and the development of coal industry;②By a review and a comparative analysis of characteristics of the traditional logistics demand forecasting method, it builds the grey neural network forecasting model of the coal logistics demand, so as to providing feasible ideas and methods for coal logistics demand forecasting;③Through the analysis of coal logistics demand forecasting of Shanxi Province, it puts forward the suggestions and path of coal logistics development of Shanxi Province from the macro, meso and micro three levels, so as to provide a reference basis for formulating regional relevant policies and making regional reasonable planning.The paper analyzes the characteristics of coal logistics demand forecasting, establishes the corresponding index system the demand forecasting model, does the empirical analysis combining with Shanxi Province, and puts forward policies and suggestions for coal logistics development according to the forecast results, provides strong data support for reasonable planning and development of regional economy and coal logistics, effectively avoids blind investment on coal logistics infrastructure, so as to make a match of supply and demand of coal logistics, and lays a solid foundation for the sustainable development of coal resources and the extension of coal industry chain.