Fate is magical.If it were two or three years earlier,Chunchun(a Shanghai girl)could not have imagined that she would open a small cafe in Lhasa.The cafe’s ceiling beams have been stained by and steeped in the heavy ...Fate is magical.If it were two or three years earlier,Chunchun(a Shanghai girl)could not have imagined that she would open a small cafe in Lhasa.The cafe’s ceiling beams have been stained by and steeped in the heavy flavor of coffee for hundreds of years.From the cafe,you can see Lhamzesha,which lies only 50 meters away from the Jokhang Temple.Looking out from the balcony of Chunchun’s studio,you can see the golden roof of the Jokhang Temple as dazzling as fire.Chunchun’s Turn Around Back to the cafe with its azure ceilings,besides coffee there are展开更多
To implement a real-time reduction in NOx,a rapid and accurate model is required.A PLS-ELM model based on the combination of partial least squares(PLS)and the extreme learning machine(ELM)for the establishment of the ...To implement a real-time reduction in NOx,a rapid and accurate model is required.A PLS-ELM model based on the combination of partial least squares(PLS)and the extreme learning machine(ELM)for the establishment of the NOx emission model of utility boilers is proposed.First,the initial input variables of the NOx emission model are determined according to the mechanism analysis.Then,the initial input data is extracted by PLS.Finally,the extracted information is used as the input of the ELM model.A large amount of real data was obtained from the distributed control system(DCS)historical database of a 1 000 MW power plant boiler to train and validate the PLS-ELM model.The modeling performance of the PLS-ELM was compared with that of the back propagation(BP)neural network,support vector machine(SVM)and ELM models.The mean relative errors(MRE)of the PLS-ELM model were 1.58%for the training dataset and 1.69%for the testing dataset.The prediction precision of the PLS-ELM model is higher than those of the BP,SVM and ELM models.The consumption time of the PLS-ELM model is also shorter than that of the BP,SVM and ELM models.展开更多
文摘Fate is magical.If it were two or three years earlier,Chunchun(a Shanghai girl)could not have imagined that she would open a small cafe in Lhasa.The cafe’s ceiling beams have been stained by and steeped in the heavy flavor of coffee for hundreds of years.From the cafe,you can see Lhamzesha,which lies only 50 meters away from the Jokhang Temple.Looking out from the balcony of Chunchun’s studio,you can see the golden roof of the Jokhang Temple as dazzling as fire.Chunchun’s Turn Around Back to the cafe with its azure ceilings,besides coffee there are
基金The National Natural Science Foundation of China(No.71471060)Natural Science Foundation of Hebei Province(No.E2018502111)
文摘To implement a real-time reduction in NOx,a rapid and accurate model is required.A PLS-ELM model based on the combination of partial least squares(PLS)and the extreme learning machine(ELM)for the establishment of the NOx emission model of utility boilers is proposed.First,the initial input variables of the NOx emission model are determined according to the mechanism analysis.Then,the initial input data is extracted by PLS.Finally,the extracted information is used as the input of the ELM model.A large amount of real data was obtained from the distributed control system(DCS)historical database of a 1 000 MW power plant boiler to train and validate the PLS-ELM model.The modeling performance of the PLS-ELM was compared with that of the back propagation(BP)neural network,support vector machine(SVM)and ELM models.The mean relative errors(MRE)of the PLS-ELM model were 1.58%for the training dataset and 1.69%for the testing dataset.The prediction precision of the PLS-ELM model is higher than those of the BP,SVM and ELM models.The consumption time of the PLS-ELM model is also shorter than that of the BP,SVM and ELM models.
