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优化随机森林模型的网络故障预测 被引量:8
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作者 邱少明 杨雯升 +1 位作者 杜秀丽 王雪珂 《计算机应用与软件》 北大核心 2021年第2期103-109,170,共8页
随机森林是一种组合分类器技术,相较于决策树等单分类器,具有更好的预测和分类性能,但其也存在一些问题:因为随机森林自身的随机性,导致预测结果存在波动性;所使用的原始数据集样本基数大,维数多,增加了随机森林组合分类器的训练时间。... 随机森林是一种组合分类器技术,相较于决策树等单分类器,具有更好的预测和分类性能,但其也存在一些问题:因为随机森林自身的随机性,导致预测结果存在波动性;所使用的原始数据集样本基数大,维数多,增加了随机森林组合分类器的训练时间。针对以上问题,提出优化随机森林模型,对数据集进行数据集预处理和PCA降维操作,引入累计贡献率。结合选择的最佳阈值进行最终的预测结果分类,提高了模型的训练速度、预测准确率和稳定性。实验证明,该方法具有更优越的预测性能。 展开更多
关键词 故障预测 随机森林机器学习 PCA降维
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Application of optimized random forest regressors in predicting maximum principal stress of aseismic tunnel lining
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作者 MEI Xian-cheng DING Chang-dong +4 位作者 ZHANG Jia-min LI Chuan-qi CUI Zhen SHENG Qian CHEN Jian 《Journal of Central South University》 CSCD 2024年第11期3900-3913,共14页
Using flexible damping technology to improve tunnel lining structure is an emerging method to resist earthquake disasters,and several methods have been explored to predict mechanical response of tunnel lining with dam... Using flexible damping technology to improve tunnel lining structure is an emerging method to resist earthquake disasters,and several methods have been explored to predict mechanical response of tunnel lining with damping layer.However,the traditional numerical methods suffer from the complex modelling and time-consuming problems.Therefore,a prediction model named the random forest regressor(RFR)is proposed based on 240 numerical simulation results of the mechanical response of tunnel lining.In addition,circle mapping(CM)is used to improve Archimedes optimization algorithm(AOA),reptile search algorithm(RSA),and Chernobyl disaster optimizer(CDO)to further improve the predictive performance of the RFR model.The performance evaluation results show that the CMRSA-RFR is the best prediction model.The damping layer thickness is the most important feature for predicting the maximum principal stress of tunnel lining containing damping layer.This study verifies the feasibility of combining numerical simulation with machine learning technology,and provides a new solution for predicting the mechanical response of aseismic tunnel with damping layer. 展开更多
关键词 maximum principal stress aseismic tunnel lining random forest regressor machine learning
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