BP神经网络的通风系统可靠性评价  

Ventilation system reliability evaluation based on BP neural network

作　　者：卢国斌[1] 陈鹏[1] 张俊武[1] 

机构地区：[1]辽宁工程技术大学矿业学院,辽宁阜新123000

出　　处：《辽宁工程技术大学学报（自然科学版）》2014年第1期23-27,共5页Journal of Liaoning Technical University (Natural Science)

摘　　要：为了找到一种更加准确、快速评价矿井通风系统可靠性的方法.通过定量分析影响矿井通风系统的各因素,建立完整有效的评价指标体系.利用BP神经网络映射评价指标体系和可靠性等级之间的非线性关系,建立评价模型,由Matlab编程确定评价模型各参数,提高了预测速度和精度.用Visual Basic建立了图形用户界面,简化操作流程.结果表明:该评价指标体系结构完整,能够充分描述通风系统的安全状况.所建立的BP神经网络可以正确映射通风系统可靠等级,且仅通过图形用户界面即可完成矿井通风系统安全可靠性的预测工作.This paper aimed to find a more accurate and rapid method to evaluate the reliability of mine ventilation system. By quantitative analysis of various factors which can impact the mine ventilation system, this study established a complete and effective evaluation system. By using of the BP neural network to map the non-linear relationship between the evaluation index system and the levels of reliability, this study established the evaluation model, and found out parameters of the evaluation model through matlab programming, which actually improved the speed and accuracy of the prediction. The operation is streamlined by creating Visual Basic graphic user interface. It can be inferred from the result that the evaluation index system has an integrated structure and can adequately describe the security situation of the ventilation system.The BP neural network established by this means can correctly map the reliability level of ventilation system, and complete the security and reliability forecasting of mine ventilation system only through the graphical user interface.

关 键 词：通风系统评价 评价指标体系 BP神经网络 MATLAB VISUAL Basic 

分 类 号：TD724[矿业工程—矿井通风与安全]