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Research On The Evaluation Of Regional Energy-saving Effect Based On Uncertainty

Posted on:2009-03-28Degree:MasterType:Thesis
Country:ChinaCandidate:W H WangFull Text:PDF
GTID:2189360272477408Subject:Systems Engineering
Abstract/Summary:PDF Full Text Request
The energy is very important as a production factor. Our country is in the period of high-speed economic development, the demand for energy is very great, but our own supply is limited. Saving energy is the inevitable choice to alleviate the energy restriction, lighten the environmental pressure, ensure the economic security and realize the sustainable development. Our country is vast in territory, the condition of the energy using is quite different in different areas, and the regional difference of energy-saving effects is very obvious.According to regional different characteristic, the paper has chosen the regional difference of energy-saving effects as the research object and used many methods about systems science of uncertainty to comprehensively evaluate China's regional energy-saving effect through setting up the evaluation index system of regional energy-saving effect. Having introduced relevant research backgrounds in detail, we use the method of Derivable Delphi to establish the evaluation index system on the basis of the scholars'research results. The paper has confirmed the weight of every index in the method of investigating experts and then evaluated the weights by reformative triangular whitenization weight function. We use Grey-Clustering Analysis to divide 30 provinces in our country into four big classes. Based on the confirmed weight, we use the method of Dynamic multi-scale evaluation to evaluate the provinces of every class and analyze the related factors of per unit GDP by grey correlation to draw their related degree and size of the influence power.The paper has used the model of GM(1,1) to predict the energy-saving effects in the following five years scientifically, and analyzed the concrete conditions of energy-saving effects about all classes of provinces, then put forward the further striving direction in the future pointedly. Finally, we point out countermeasure and suggestion of promoting the energy-saving effects in the height of the country.
Keywords/Search Tags:Energy-saving effects, Regional Classification, Comprehensively evaluation, Uncertainty, Whitenization weight function, Grey-Clustering, GM(1,1)
PDF Full Text Request
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