基于SHO-SVM的火法炼铜工艺风险评估研究
Risk Assessment Study of Thermal Copper Refining Process Based on SHO-SVM
王振1
作者信息
- 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
- 折叠
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.
Abstract
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.
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Key words
pyro-copper refining process/spotted hyena optimization algorithm/support vector machine/risk assessment引用本文复制引用
出版年
2024
NETL
NSTL
万方数据