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采用DEA方法测算了2005-2012年我国大陆30个地区工业能源利用效率的平均水平,通过相关分析确定能源效率的影响因素,并运用多层感知器神经网络模型对工业能源效率的影响因素进行重要性分析.结果显示:1)除少数省份能源得到充分有效利用外,其余省份都存在能源投入的冗余,特别是中西部地区的投入冗余量较多,其节能潜力较大;2)技术水平、研发强度、劳动生产率、国有化程度、市场开放程度对能源效率有显著影响,产业结构和工业企业平均规模无显著影响;3)按照对能源效率的影响程度排序,依次是市场开放程度、技术水平、研发强度、劳动生产率、国有化程度.
The DEA method was used to calculate the average level of industrial energy use efficiency in 30 regions of mainland China from 2005 to 2012. The correlation analysis was used to determine the influencing factors of energy efficiency and the multi-layer perceptron neural network model was used to evaluate the influencing factors of industrial energy efficiency The results show that: 1) Except for a few provinces where energy is fully and effectively utilized, there are redundant energy inputs in other provinces, especially in the central and western regions, where there is more redundancy and a greater potential for energy conservation. 2) Technology Level, R & D intensity, labor productivity, nationalization degree and market openness have a significant impact on energy efficiency, and the average size of industrial structure and industrial enterprises has no significant effect; 3) According to the degree of impact on energy efficiency, followed by market openness, Technical level, research and development intensity, labor productivity, nationalization level.