An improved neural network based on L-M algorithm has been applied to fault diagnosis expert system against to the slow convergence rate of conventional BP neural network.
针对传统BP神经网络训练中收敛速度较慢的缺点，提出一种基于L - M算法的神经网络应用于机械设备故障诊断的专家系统。
Theoretical analysis proves that the M-PSO algorithm keeps convergence.
通过理论分析，证明算法具有良好的收敛性。
The network could predict the effects of the temperature on the boundary film strength. the network trained with the L-M rule were quick in convergence and small in error.
该模型可用于准确地预测温度对边界膜强度的影响。并采用L - M规则进行神经网络学习训练可使网络收敛快，误差小。
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