Based on the characteristics of natural gas demand trend, this paper proposed ARIMA model which can predict China's natural gas demand as an effective tool. Compared with the RBF neural network model and combined model, empirical results show that the accuracy and stability of the ARIMA model is best.
The article gives comparative analysis of basic reserves variation of China’s fundamental energy resources during 2002-2012, including coal, petroleum and natural gas. The results show that
the growth of China’s fundamental energy resources basic reserves has entered a relatively stable period except coal. After analyzing the basic reserves variation, the change tendency can be obtained.
Finally clarify the influencing factors which lead to the change, and put forward some relevant policy and recommendations.
Assuming in the perfectly competitive market, using the optimal control theory and making the social welfare as the maximization target, the paper studies on environment control which impacts the optimal extraction path of exhaustible resource. The special case result shows that: reserve and the changes of environment capacity function and curve are influenced by original reserve, discounted value, the absolute ratio of green environment flow to resource extraction quantity, and marginal cost.
Energy demand system is a complex system, which is affected and controlled by many factors and external environmental in its development and evolution process. This paper selected the prediction method of correlation, in the way of literature review at first, preliminary qualitatively choose factors which influence the energy demand. Then the direct, indirect and total effect degree of each factor on energy demand were measured by the method of path analysis. On the basis of path analysis, used ridge regression to eliminate multicollinearity to forecast China's energy demand, the prediction accuracy is high, and its practicability in this model is good.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.