基于蛇算法优化的改进RBF神经网络的航天电磁继电器贮存寿命预测方法OA

Aiming at the prediction and prediction accuracy of contact resistance of aerospace electromagnetic relays,a radial basis function(BRF)neural network model based on snake optimization(SO)algorithm is proposed.On the basis of the traditional RBF model,the SO algorithm is used to optimize the weight parameters so as to better predict the contact resistance value of the relay.The constructed SO-RBF prediction model is compared with RBF model.The models are used to predict the change trend of contact resistance.The comparison and analysis of the prediction results show that the proposed model has high prediction accuracy.