disp(['SAPSO-BP训练集数据的MAE为:', num2str(mae22)]) disp(['CSAPSO-BP训练集数据的MAE为:', num2str(mae33)]) disp(['PSO-BP测试集数据的MAE为:', num2str(mae1)]) disp(['SAPSO-BP测试集数据的MAE为:', num2str(mae2)]) disp(['CSAPSO-BP测试集数据的MAE为:', num2str(mae3)]) % ...
Using the traditional BP neural networks for prediction is prone to falling into local minima, resulting in compensation failure. In this paper, the zero-biased temperature compensation model of fiber optic gyroscope adopting the chaos simulated annealed particle swarm BP (C...
To address the problem of the quantitative identification of glass panel surface defects, a new method combining the chaotic simulated annealing particle swarm algorithm (CSAPSO) and the BP neural network is proposed for the quantitative evaluation of microwave detection signals of glass panel defects....