金融研究
金融研究
금융연구
Journal of Financial Research
2013年
7期
87~98
,共null页
高校节能减排 BP神经网络 效果评价
高校節能減排 BP神經網絡 效果評價
고교절능감배 BP신경망락 효과평개
University energy saving and emission reduction, BP Neural Network, Effect evaluation
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。
公共事業部門的能源消耗問題正在逐漸引起人們的重視。中國作為髮展中大國，製度的不健全導緻公共事業部門消耗越來越多的能源。教育行業作為不可缺少的公共事業行業，由于其非盈利性和壟斷性，能耗問題對節能減排的影響越來越大。本文通過對全國高校調查問捲的分析，採用主成分分析和BP神經網絡模型構建瞭高校節能減排的評價指標體繫，併通過建立Tobit模型分析影響因素，研究瞭節能減排在高校的開展情況。本文髮現，不同省份的高校節能減排效果存在不同，主要反映為北京、上海、廣東等經濟髮達地區高校節能減排開展情況最好，其他地區的差異併不明顯。影響高校節能減排的主要因素是學校的差異，211院校開展的效果明顯好于其他高校；其次為高校教師結構；同時地區開放程度具有比較顯著的影響；政府加大環保方麵的財政投入有利于高校節能減排的開展。
공공사업부문적능원소모문제정재축점인기인문적중시。중국작위발전중대국，제도적불건전도치공공사업부문소모월래월다적능원。교육행업작위불가결소적공공사업행업，유우기비영리성화롱단성，능모문제대절능감배적영향월래월대。본문통과대전국고교조사문권적분석，채용주성분분석화BP신경망락모형구건료고교절능감배적평개지표체계，병통과건립Tobit모형분석영향인소，연구료절능감배재고교적개전정황。본문발현，불동성빈적고교절능감배효과존재불동，주요반영위북경、상해、엄동등경제발체지구고교절능감배개전정황최호，기타지구적차이병불명현。영향고교절능감배적주요인소시학교적차이，211원교개전적효과명현호우기타고교；기차위고교교사결구；동시지구개방정도구유비교현저적영향；정부가대배보방면적재정투입유리우고교절능감배적개전。
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.
