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Avionics System Failure Prediction Based on Bacteria Evolution and Gray Neural Network

机译:基于细菌进化和灰色神经网络的航空电子系统故障预测

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Aiming at the problem of the gray neural network easy to fall into local optimization, a failure prediction algorithm with bacterial evolutionary and gray neural network is proposed. First, a gray neural network fault detection model is established. Then, the bacterial evolutionary algorithm is selected to optimize the initial weights and thresholds of the network to solve the defect of network easy to fall into local optimization. Finally, several kinds of fault prediction effect of the algorithm are compared through the simulation experiment. The simulation results show that the algorithm combining bacterial evolutionary and gray neural network can achieve optimal prediction effect quickly.
机译:针对灰色神经网络容易陷入局部优化的问题,提出了一种基于细菌进化和灰色神经网络的故障预测算法。首先,建立了灰色神经网络故障检测模型。然后,选择细菌进化算法对网络的初始权重和阈值进行优化,以解决网络容易陷入局部优化的缺陷。最后,通过仿真实验比较了该算法的几种故障预测效果。仿真结果表明,结合细菌进化和灰色神经网络的算法可以快速达到最优的预测效果。

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