摘要
利用3E评价模型构建炼油企业的综合能源效率评价指标体系,通过运用BP神经网络确定评价指标的权重,权重最高的指标是资源循环利用率,其次是能源强度。利用2010年M企业和炼油行业的数据进行神经网络训练,结果显示,M企业的综合能源效率评价结果明显优于行业水平。
3E evaluation model is employed to analyze the comprehensive factors affecting energy efficiency in refining enterprise, and the BP neural network is adopted to determine the weights of the evaluation index. The result shows that the highest weight of the indicators is the resource recycling rate, followed by energy intensity. Put 2010 M enterprise and refining industry data into the neural network training, the results show that the evaluation of the energy efficiency of the M enterprises is significantly better than the industrial level.
出处
《北京石油化工学院学报》
2013年第2期56-61,共6页
Journal of Beijing Institute of Petrochemical Technology
关键词
炼油企业
能源效率
BP神经网络
oil refining enterprises
energy efficiency
BP neural network
