基于BP神经网络的煤矿通风系统安全评价

研究了BP神经网络的结构和L-M学习算法的步骤,通过分析煤矿通风系统,建立了多因素控制的煤矿安全评价指标体系。在此基础上,运用Matlab编制BP网络程序并利用导师信号对网络进行训练,建立了煤矿通风系统安全评价模型。仿真结果表明待校验样本的安全等级与实际情况相符,L-M算法收敛速度也满足要求。

Safety Evaluation of Coal Mine Ventilation System Based on BP Neural Network

It studied the structure of BP neural network and the steps of L-M learning algorithm.Through the analysis of coal mine ventilation system,the index system of coal mine safety evaluation which was controlled by many factors was established.On this basis,it compiled BP network program with Matlab,and trained the network by mentor signal,thus it set up safety evaluation model of coal mine ventilation system.The simulation results showed that the safety level of the sample was in accordance with the actual situation,the convergence rate of L-M algorithm could meet the requirements.