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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。
The structure of BP neural network and the steps of L-M learning algorithm are studied. By analyzing coal mine ventilation system, a multi-factor coal mine safety evaluation index system is established. On this basis, the use of Matlab programming BP network program and the use of instructor signals to train the network, established a mine ventilation system safety evaluation model. The simulation results show that the security level of the sample to be calibrated is in accordance with the actual situation, and the convergence speed of L-M algorithm also meets the requirements.