Product process parameter prediction based on integrated ELM-ANFIS

Due to the complexity of process-based processing, it is difficult to accurately locate the quality factors of final products into specific production links and parameters. The prediction of parameters based on the collected data can improve the production efficiency and processing quality. Based on the integration of extreme learning machine and adaptive neural fuzzy inference system parameters prediction model is established, the results show that compared with the single machine learning method, the proposed algorithm model has higher prediction accuracy, at last, through actual production parameter test proved that the model has good prediction performance and generalization performance.