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The Modeling and Predictive Analysis of Chinese Coal Demand

Author: ZhangChangWang
Tutor: WangJianHua
School: Shanxi University of Finance
Course: Statistics
Keywords: Coal demand Cointegration BP neural network Forecast
CLC: F426.21
Type: Master's thesis
Year: 2009
Downloads: 152
Quote: 3
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Abstract


This paper first analyzes the factors that affect the demand for coal in China , and summarizes the main method of coal demand forecast . To establish the cointegration models between coal demand in China and the main factors , the long-term stable equilibrium relationship between coal demand in China and the main influencing factors , the model test showed that rail freight capacity and industrial output is the most important factor affecting China's coal demand . On this basis , the establishment of the error correction model to study the short-term behavior of China 's coal demand . The BP (Back-Propagation) neural network model , followed by the establishment of China's coal demand by constructing reasonable BP neural network diagram , the selected training samples to train the model fitting results of the inspection and test samples , get the right nerve predictable network , predict results show that 5.00% of the next five years , the average annual growth rate of China 's coal demand . Finally, some policy recommendations to improve the imbalance between supply and demand of coal from the two aspects of the energy and economic development .

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CLC: > Economic > Industrial economy > China Industrial Economy > Industrial sector economy
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