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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.
In order to find a more accurate and rapid method to evaluate the reliability of mine ventilation system, a comprehensive and effective evaluation index system is established by quantitatively analyzing the various factors that affect the mine ventilation system.By using BP neural network mapping between evaluation index system and reliability level , The evaluation model was established and the parameters of the evaluation model were determined by Matlab programming to improve the prediction speed and accuracy.The graphical user interface was established by Visual Basic to simplify the operation flow.The results showed that the evaluation index system is complete and fully capable Describe the safety of ventilation system.The established BP neural network can correctly map the reliability of ventilation system and can only predict the safety and reliability of mine ventilation system through a graphical user interface.