公共事业部门的能源消耗问题正在逐渐引起人们的重视.中国作为发展中大国,制度的不健全导致公共事业部门消耗越来越多的能源.教育行业作为不可缺少的公共事业行业,由于其非盈利性和垄断性,能耗问题对节能减排的影响越来越大.本文通过对全国高校调查问卷的分析,采用主成分分析和BP神经网络模型构建了高校节能减排的评价指标体系,并通过建立Tobit模型分析影响因素,研究了节能减排在高校的开展情况.本文发现,不同省份的高校节能减排效果存在不同,主要反映为北京、上海、广东等经济发达地区高校节能减排开展情况最好,其他地区的差异并不明显.影响高校节能减排的主要因素是学校的差异,211院校开展的效果明显好于其他高校;其次为高校教师结构;同时地区开放程度具有比较显著的影响;政府加大环保方面的财政投入有利于高校节能减排的开展.More attention is focused on the energy consumption of the public sector. As a developing country, the imperfection of the China's system results in the public sector to consume more and more energy. Education is indispensable for public utilities industry, because of their non - profit and monopoly, the energy consumption problem effect on energy saving and emission reduction has more and more influence. We have carried out a questionnaire survey on Chinas universities, and adopt the Principal Component Analysis approach and the BP Neural Network Model to set up the evaluation index system for energy saving and emission reduction of the Chi- nese universities. We further set up the Tobit model to analyze the related impacting factors, and study the im- plementation of university energy saving and emission reduction. It is found that the effects of energy saving and emission reduction in universities of different regions are quite different. University energy saving and emission reduction is carried out best in developed regions such as Beijing, Shanghai and Guangzhou, but the difference among other regions is not significant. The most important factor influencing university energy saving and emission reduction is the divergence in universities: implementation effects of "211 " universities are much better than other universities. University teacher structure and regional openness are also two important impacting factors. In addition, higher financial input by the government on environment protection can promote the implementation of energy saving and emission reduction in Chinese universities.
高校节能减排 BP神经网络 效果评价