In order to effectively improve the accuracy of the thermal error prediction model based on nonlinear time series, the cluster number of fuzzy C mean clustering was determined by statistical test, and the key temperature measurement points were sorted and selected by combining the grey correlation analysis with different dimensionless processing. The thermal error prediction model based on NARX neural network was established; by setting the ranges of the input delay order, output delay order and the number of hidden neurons, the mind evolutionary algorithm was used to optimize the input and output delay order and the number of hidden neurons. Compared with the NARX neural network prediction model with randomly selected parameters, the prediction accuracy of the model is improved by 36.98%.
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孙昂,王丽爽,谢新连.基于MEA-NARX神经网络主轴热误差建模[J].机床与液压,2022,50(24):49-53. SUN Ang, WANG Lishuang, XIE Xinlian. Modeling of Spindle Thermal Error Based on MEA-NARX Neural Network[J]. Machine Tool & Hydraulics,2022,50(24):49-53