基于SHO-SVM的火法炼铜工艺风险评估研究  

Risk Assessment Study of Thermal Copper Ref ining Process Based on SHO-SVM

作　　者：王振 WANG Zhen(Liaoning Testing and Certif ication Center(Liaoning Academy of Safety Science),Shenyang 110004,China)

机构地区：[1]辽宁省检验检测认证中心(辽宁省安全科学研究院),辽宁沈阳110004

出　　处：《化工管理》2024年第19期68-70,共3页Chemical Management

摘　　要：为准确判断火法炼铜工艺风险等级,文章提出了一种精准有效的风险评估模型。基于火法炼铜工艺按功能区段筛选出人员、环境、设备、管理四方面的20项风险指标因素,利用斑点鬣狗优化算法(SHO)寻优支持向量机(SVM)的正则因数与核参数,建立SHO-SVM风险评估模型。结果表明,该模型正确分类了21组数据的风险等级,判别准确率为87.5%,在各项性能指标上均优于对照模型,表明其对电火法炼铜工艺风险评估等级具备高识别精度。In order to accurately determine the risk level of pyro-copper ref ining 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 ref ining process,the spotted hyena optimization algorithm(SHO)is used to f ind 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 classif ies 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 ref ining process.

关 键 词：火法炼铜工艺 斑点鬣狗优化算法 支持向量机 风险评估 

分 类 号：X937[环境科学与工程—安全科学]