首站-论文投稿智能助手
典型文献
Quantitative Analysis of Methanol in Methanol Gasoline by Calibration Transfer Strategy Based on Kernel Domain Adaptive Partial Least Squares(kda-PLS)
文献摘要:
The application of near-infrared(NIR)spectroscopy combined with multivariate calibration methods can achieve the rapid analysis of methanol gasoline.However,instrumental or environmental differences found for spectra make it impossible to continuously apply the previously developed calibration model.Therefore,the calibration transfer technique would be required to solve the time-consuming and laborious problem of reestablishing a new model.In this work,a calibration transfer method named kernel domain adaptive partial least squares(kda-PLS)was applied to the calibration transfer from the primary instrument to the secondary ones.Firstly,wavelet transform(WT)and variable importance in projection(VIP)were employed to enhance the predictive performance of the kda-PLS transfer model.Then,the results found for the calibration transfer by piecewise direct standardization(PDS)and domain adaptive partial least squares(da-PLS)were compared to verify the calibration transfer(CT)effect of kda-PLS.The results point that the kda-PLS method can transfer the PLS model developed on the primary instrument to the secondary ones,and achieve results comparable to the those of reestablishing a new PLS model on the secondary instrument,with RP2=0.9979(RP2:coefficients of determination of the prediction set),RMSEP=0.0040(RMSEp:root mean square error of the prediction set),and MREp=3.03%(MREp:mean relative error of the prediction set).Therefore,kda-PLS will provide a new method for quantitative analysis of methanol content in methanol gasoline.
文献关键词:
作者姓名:
XU Yanyan;LI Maogang;FENG Ting;JIAO Long;WU Fengtian;ZHANG Tianlong;TANG Hongsheng;LI Hua
作者机构:
Key Laboratory of Synthetic and Natural Functional Molecule of the Ministry of Education,College of Chemistry&Materials Science,Northwest Univer-sity,Xi'an 710127,P.R.China;College of Chemistry and Chemical Engineering,Xi'an Shiyou University,Xi'an 710065,P.R.China
引用格式:
[1]XU Yanyan;LI Maogang;FENG Ting;JIAO Long;WU Fengtian;ZHANG Tianlong;TANG Hongsheng;LI Hua-.Quantitative Analysis of Methanol in Methanol Gasoline by Calibration Transfer Strategy Based on Kernel Domain Adaptive Partial Least Squares(kda-PLS))[J].高等学校化学研究(英文版),2022(04):1057-1064
A类:
reestablishing,MREp
B类:
Quantitative,Analysis,Methanol,Gasoline,by,Calibration,Transfer,Strategy,Based,Kernel,Domain,Adaptive,Partial,Least,Squares,kda,PLS,application,near,infrared,NIR,spectroscopy,combined,multivariate,calibration,methods,can,achieve,rapid,analysis,methanol,gasoline,However,instrumental,environmental,differences,found,spectra,make,impossible,continuously,apply,previously,developed,model,Therefore,transfer,technique,would,be,required,solve,consuming,laborious,problem,new,In,this,work,named,kernel,domain,adaptive,partial,least,squares,was,applied,from,primary,secondary,ones,Firstly,wavelet,transform,WT,variable,importance,projection,VIP,were,employed,enhance,predictive,performance,Then,results,piecewise,direct,standardization,PDS,compared,verify,effect,point,that,comparable,those,RP2,coefficients,determination,prediction,set,RMSEP,RMSEp,root,mean,error,relative,will,provide,quantitative,content
AB值:
0.511437
相似文献
A Novel Early Warning Model for Hand, Foot and Mouth Disease Prediction Based on a Graph Convolutional Network
JI Tian Jiao;CHENG Qiang;ZHANG Yong;ZENG Han Ri;WANG Jian Xing;YANG Guan Yu;XU Wen Bo;LIU Hong Tu-NHC Key Laboratory of Medical Virology and Viral Diseases,National Institute for Viral Disease Control and Prevention,Chinese Center for Disease Control and Prevention,Beijing 100026,China;Academy of Cyber Science and Engineering,Southeast University,Nanjing 211189,Jiangsu,China;Center for Biosafety Mega Science,Chinese Academy of Sciences,Wuhan 430071,Hubei,China;Guangdong Center for Disease Control and Prevention,Guangzhou 511430,Guangdong,China;Shandong Center for Disease Control and Prevention,Jinan 250014,Shandong,China;LIST,Key Laboratory of Computer Network and Information Integration(Southeast University),Ministry of Education,Southeast University,Nanjing 211189,Jiangsu,China
A Predictive Nomogram for Predicting Improved Clinical Outcome Probability in Patients with COVID-19 in Zhejiang Province,China
Jiaojiao Xie;Ding Shi;Mingyang Bao;Xiaoyi Hu;Wenrui Wu;Jifang Sheng;Kaijin Xu;Qing Wang;Jingjing Wu;Kaicen Wang;Daiqiong Fang;Yating Li;Lanjuan Li-State Key Laboratory for Diagnosis and Treatment of Infectious Diseases,National Clinical Research Center for Infectious Diseases,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases,The First Affiliated Hospital,College of Medicine,Zhejiang University,Hangzhou 310003,China;State Key Laboratory of Genetic Engineering,Institute of Biostatistics,School of Life Sciences,Fudan University,Shanghai 200433,China;Division of Hepatobiliary and Pancreatic Surgery,Department of Surgery,Key Lab of Combined Multi-organ Transplantation of the Ministry of Health,The First Affiliated Hospital,College of Medicine,Zhejiang University,Hangzhou 310003,China;Division of of Endocrinology and Metabolism,Department of Internal Medicine System,The First Affiliated Hospital,College of Medicine,Zhejiang University,Hangzhou 310003,China
Factors Predicting Progression to Severe COVID-19:A Competing Risk Survival Analysis of 1753 Patients in Community Isolation in Wuhan,China
Simiao Chen;Hui Sun;Mei Heng;Xunliang Tong;Pascal Geldsetzer;Zhuoran Wang;Peixin Wu;Juntao Yang;Yu Hu;Chen Wang;Till B?rnighausen-Chinese Academy of Medical Sciences & Peking Union Medical College,Beijing 100730,China;Heidelberg Institute of Global Health(HIGH),Faculty of Medicine and University Hospital,Heidelberg University,Heidelberg 69120,Germany;Institute of Hematology,Union Hospital,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430022,China;Department of Pulmonary and Critical Care Medicine,Beijing Hospital,Beijing 100730,China;National Center of Gerontology,Institute of Geriatric Medicine,Beijing 100730,China;Division of Primary Care and Population Health,Department of Medicine,Stanford University,Stanford,CA 94305,USA;Peking Union Medical College Hospital,Beijing 100730,China;State Key Laboratory of Medical Molecular Biology,Institute of Basic Medical Sciences,Chinese Academy of Medical Sciences & Peking Union Medical College,Beijing 100730,China;National Clinical Research Center for Respiratory Diseases,Beijing 100029,China;Department of Pulmonary and Critical Care Medicine,Center of Respiratory Medicine,China-Japan Friendship Hospital,Beijing 100029,China
机标中图分类号,由域田数据科技根据网络公开资料自动分析生成,仅供学习研究参考。