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基于支持向量机与连续蚁群算法建立的煤矿企业安全投入模型研究

Research on Safety Investment Model of Coal Mine Enterprises based on Support Vector Machine and Continuous Ant Colony Algorithm

  • 摘要: 为了解决当前我国煤矿企业存在的安全投入不足和安全投入不合理等问题,提出了一种集成支持向量机(SVM)与连续蚁群算法(CACA)的安全投入模型。将煤矿安全投入划分为工业卫生投资、安全技术投资、安全管理投资、安全教育投资和劳保用品投资等5项,利用SVM建立安全投入与安全保障度之间的非线性映射,在保证一定安全保障度的前提下,利用CACA迭代寻找最优的安全投入方案。研究结果表明:该方案可优化分配各项安全投入资金,避免了不必要的浪费及投入不足等问题。证明集成了SVM与CACA的安全投入模型应用的可行性,可对其进行更加深入的研究,以指导煤矿企业进行科学合理的安全投入。

     

    Abstract: In order to solve the problems that the safety investment was insufficient and unreasonable in domestic coal mine enterprises, a safety investment model based on integrated support vector machine (SVM) and continuous ant colony algorithm (CACA) was proposed. The investment of coal mine safety was divided into five items, namely industrial health investment, safety technology investment, safety management investment, safety education investment and labor protection supplies investment, the nonlinear mapping between safety investment and safety guarantee degree was established by SVM, CACA iteration was used to find the optimal security input scheme under the premise of ensuring a certain degree of security. The results show that the scheme can optimize the allocation of security investment funds, avoid waste and inadequate investment and other problems. It proves the feasibility of the application of the safety investment model that integrated SVM and CACA, which can be further studied to guide coal mine enterprises to make scientific and reasonable safety investment.

     

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