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China's Demand For Oil And Gas Resources

Posted on:2005-12-25Degree:MasterType:Thesis
Country:ChinaCandidate:Z L ZhouFull Text:PDF
GTID:2206360122493018Subject:Applied Mathematics
Abstract/Summary:PDF Full Text Request
Many Chinese scholars have done plenty of researches on energy sources and have achieved a lot in this area. Looking back toward the history of China's consumption of energy sources, we can safely say that oil and gas consumption is of great importance in that they, as one of the essential proportion of energy resources, not only contribute to national economic development, but have also become an international strategic resources. With the development of science and technology, great efficiency and economic advances have been achieved. The problem, in this case, arises. How can we evaluate the consumption demand of oil and gas in our macro-economic development? Can our oil and gas be self-sufficient and thus lay a solid foundation for our further economic development? This paper is an attempt to explore China's demand of oil and gas in near future's realization of economic growth.In recent years, Weng cycle life Model, Logistic Mode, Grey Model, two-Way Control Model, Random Method etc. are often used to study oil and gas reserves and output. This paper, however, avoiding just making use of data concerning oil and gas consumption, turns to investigate economic factors in relation to energy consumption, and sets up genetic neural network model and time order model so that function relations are established between economic factors and energy consumption. By utilizing combinatorial forecast principle and its model, when taking China's national economic goal into our consideration, the national consumption demand in near future of China is reasonably concluded-In 2010, the energy consumption of China is equal to that of 1,723,000,000 tons of coal, among which petroleum accounts for 434,000,000 tons of equivalent coal, gas 96,470,000 tons of equivalent coal; in 2020, the figures are respectively 1,095,000,000, 295,000,000, 107,000,000 tons of equivalent coal.
Keywords/Search Tags:the Energy Consumption of Every Unit, Genetic Algorithm, Artificial Neural Network, Confidential Interval, time sequence, combinatorial prediction
PDF Full Text Request
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