School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China, 510640;
rnSchool of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China, 510640 School of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China;
School of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China Shenzhen Key laboratory of mould advanced manufacture, Shenzhen, China, 518060;
rnSchool of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China, 510640;
KPCA; LS-SVM; prediction; hydrogen gas concentration;
机译:基于KPCA和LS-SVM的振动筛效率预测建模方法
机译:基于KPCA和LS-SVM的振动屏效率预测的建模方法
机译:基于KPCA-MABC-SVR模型的油气管道运输系统中管道的外部腐蚀速率的准确预测
机译:PAR减少小规模模式容器中氢气浓度的核废料长期贮存容器功效的基础实验研究
机译:源对大气有机化合物浓度的贡献:排放量测量和模型预测。
机译:ARIMA和最小二乘支持向量机(LS-SVM)模型用于预测受灾最严重国家中SARS-CoV-2确诊病例的研究
机译:基于KpCa-FFOa-GRNN模型的变压器油中溶解气体浓度预测
机译:两种高斯模型(CRsTER和改进CRsTER)的预测与对流条件下高层附近测得的sO2浓度的比较