机译:新型最小二乘支持向量机集成模型预测燃煤锅炉NO_x排放
The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Changping District,102206 Beijing, China;
The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Changping District,102206 Beijing, China;
The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Changping District,102206 Beijing, China;
The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Changping District,102206 Beijing, China;
NO_x emission; Coal-fired boiler; Ensemble learning; Least squares support vector machine; Partial least squares; Soft fuzzy c-means;
机译:使用支持向量回归和蚁群优化对燃煤电站锅炉NO_X排放进行建模
机译:基于最小二乘支持向量机和输出偏差更新的实时模型,用于预测燃煤电厂的NOx排放
机译:用机器学习预测燃煤CFB发电厂的SOX-NOx排放:深神经网络和最小二乘支持向量机学习的植物数据
机译:基于最小二乘支持向量机的电站锅炉NO_X发射软传感器建模
机译:与Markov模型和支持向量机模型的随机时间序列预测比较。
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Rank聚合的强大的合奏功能选择器,用于使用支持向量机开发新的VO2MAX预测模型