科研管理

科研管理 ›› 2016, Vol. 37 ›› Issue (8): 153-160.

• 论文 • 上一篇    

基于BP神经网络的中国煤炭安全评价研究

孟超1,胡健2   

  1. 1西北大学经济管理学院，陕西 西安710069;
    2西安财经学院，陕西 西安710100
  • 收稿日期:2015-10-29 修回日期:2016-02-16 出版日期:2016-08-20 发布日期:2016-08-17
  • 通讯作者: 孟超

Research on china coal mine safety evaluation based on BP neural network

Meng Chao1, Hu Jian2   

  1. 1. School of Economics and Management, Northwest University, Xi’an 710069, Shaanxi, China;
    2. Xi’an University of Finance and Economics, Xi’an 710100, Shaanxi, China
  • Received:2015-10-29 Revised:2016-02-16 Online:2016-08-20 Published:2016-08-17

摘要： 本文从资源、供需、运输、灾害、环境、市场六个方面构建涵盖供给安全和使用安全在内的煤炭安全评价体系，应用BP神经网络进行中国煤炭安全评价的实证分析。研究发现：凭借BP神经网络在能源等非线性复杂系统高效的仿真能力和逆向输出的优势，仿真训练结果准确率高，模拟预测简便易行。虽然丰富的资源储量和较高的自给水平确保了煤炭的供给安全，但CO2和SO2排放造成严重的环境问题和温室效应，使得使用安全仍是煤炭安全需要关注的焦点。今后，需要在降低煤炭在能源结构中的比重，提升电煤消费份额，大力发展洁净煤技术等方面采取有效的应对措施。

关键词: BP神经网络, 煤炭安全, 实证分析

Abstract: Including security of supply and the use of safety,construction of coal mine safety evaluation system from resources,supply and demand, transport, disaster, environmental, market, using BP neural network empirical analysis.The research shows:With BP neural network in nonlinear complex systems simulation capability efficient and reverse output advantages,the accuracy of empirical analysis is high,simulation and prediction is simple and feasible. Although the rich resources and the high level of self-sufficiency to ensure the safety of coal supply,CO2 and SO2 emissions cause serious environmental problems and the greenhouse effect, making the use of safety is still the focus of coal safety concern.We need to take effective measures to reduce the proportion of coal in the energy structure and enhance the share of power coal consumption,develop clean coal technology.

Key words:  BP neural network, coal safety, empirical analysis