煤矿企业安全管理风险预测模型研究--基于RS-SVM

摘要

Scientific risk prediction and accurate risk factors identification of coal enterprise safety management is the impor-tant premise and foundation to realize coal enterprise intrinsic safety. In order to improve the accuracy of prediction and the speed of operation, the paper builds the risk prediction model of coal enterprise safety management based on RS-SVM. First-ly, it applies the rough set theory to reduce the important risk factors of coal enterprise safety management. Secondly, it uses the SVM to train and learn the training sample. Lastly,it makes the prediction on the risk status of the test sample. The empiri-cal study proves that the model has good applicability.%科学地进行煤矿安全管理风险预测，准确找出煤矿安全管理风险因子，是实现煤矿企业本质安全的重要前提和基础。为了提高预测的精度和运算速度，文章建立了基于RS-SVM的煤矿企业安全管理风险预测模型，首先运用粗糙集理论约简出影响煤矿安全管理的重要风险因子，然后运用SVM对训练样本进行训练和学习，再对测试样本的风险状态进行预测。实证研究表明该模型具有很好的适用性。