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Comparison and Analysis of the Monte Carlo Simulation and GO Method for the Reliability of Equipment System

机译:蒙特卡罗仿真与设备系统可靠性的比较与分析

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摘要

Aiming at the problems of traditional BP neural network in fault diagnosis of equipment, the genetic algorithm is introduced to optimize the network, and the fault diagnosis model of equipment is established. The modeling ideas and considerations are introduced in detail, and the simulation calculation is carried out. The results show that the improved network has a good approximation performance, the training speed and accuracy are greatly improved, and it can be better to carry out fault diagnosis of equipment.
机译:针对传统的BP神经网络在设备故障诊断中的问题,引入了遗传算法来优化网络,建立了设备的故障诊断模型。详细介绍了建模思路和考虑因素,并进行了模拟计算。结果表明,改进的网络具有良好的近似性能,训练速度和准确性大大提高,可以更好地执行设备的故障诊断。

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