中国能源可持续发展的遗传神经网络评价

EVALUATION OF CHINA'S SUSTAINABLE DEVELOPMENT OF ENERGY BASED ON GA-BP MODEL

为了反映中国30个省(市、自治区)的能源可持续发展现状,提出有利于能源可持续发展的政策建议,该文利用国际原子能机构2005年开发完成的可持续发展能源指标体系,建立了包含14个指标的中国能源可持续发展指标体系,采用遗传神经网络模型评价了2006年各省(市、自治区)的能源可持续发展水平。结果表明:30个省(市、自治区)的能源可持续发展水平差异明显;能源贫乏省(市、自治区)比能源丰富省(市、自治区)的能源可持续发展能力高。最后根据分析结果提出了一些政策建议。

In order to reflect the current situation of sustainable development of energy of China＇ s 30 Provinces or autono- mous regions and propose energy policy recommendations for increasing the sustainable development of energy. An evaluation system for the sustainable development of energy, consisting of 14 indicators is established on the basis of energy indicators for sustainable development （EISD） published by the International Atomic Energy Agency （IAEA）. This paper uses genetic algorithm （GA）-back-propagation neural network （BPNN） model to evaluate the capacity of sustainable development of energy of China＇ s 30 Provinces or and autonomous regions in 2006. The evaluation value indicates that the relative levels among different Provinces or autonomous regions or municipalities are very obvious. The sustainable development of energy of energy poor provinces, autonomous regions or municipalities is higher than that of energy rich Provinces or autonomous regions or municipalities. Finally some energy policy recommendations are proposed.