Risk Assessment Study of Thermal Copper Refining Process Based on SHO-SVM
In order to accurately determine the risk level of pyro-copper refining process,an accurate and effective risk assessment model is proposed.Based on 20 risk indicator factors of personnel,environment,equipment and management screened by functional sections of the pyro-copper refining process,the spotted hyena optimization algorithm(SHO)is used to find the optimal regular factors and kernel parameters of the support vector machine(SVM),and the SHO-SVM risk assessment model is established.The results show that the model correctly classifies the risk level of 21 groups of data with a discrimination accuracy of 87.5%,which is better than the control model in all performance indexes,indicating that it has a high recognition accuracy for the risk assessment level of the pyro-copper refining process.
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