Prediction of Mechanical Properties of Aluminium Alloy Strip Using the Extreme Learning Machine Model Optimized by the Gray Wolf Algorithm

Mechanical properties are important indicators for evaluating the quality of strips. This paper proposes a mechanical performance prediction model based on Gray Wolf Optimization (GWO) algorithm and Extreme Learning Machine (ELM) algorithm. In modeling process, GWO is used to determine optimal weights deviations ELM experiments model’s key parameters. The effectively avoids manual intervention significantly improves aluminum alloy strips’ property accuracy. uses processed data from production plant Shandong Nanshan Aluminum Co., Ltd. as experimental data. When deviation controlled within ±10%, GWO-ELM can achieve correct rate 100% tensile strength, 97.5% yield 77.5% elongation test set. RMSE was 5.365, 11.881, 1.268, respectively. results show that has higher accuracy stability in predicting elongation. defects traditional model. It special guiding significance producing