CASIA OpenIR  > 智能制造技术与系统研究中心  > 多维数据分析
Strategy for constructing calibration sets based on a derivative spectra information space consensus
Li, Zhigang; Liu, Jiemin; Shan, Peng; et al.; Zhigang Li
Source PublicationCHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
2016-08-15
Volume156Issue:156Pages:7–13
SubtypeArticle
AbstractConstructing an excellent calibration set is crucial to ensuring accurate multivariate calibration of spectra data. The purpose of this paper is to present an improved Kennard–Stone (KS) calibration set construction strategy based on different derivative spectra information spaces, termed Consensus Kennard–Stone (CKS). The core idea is to make full use of different derivative spectra information spaces when constructing the calibration set using a consensus selection method aswell as to improve the prediction performance of the multivariate regression model. The experimental results from two public spectra datasets indicate that the proposed CKS strategy can use a more appropriate subset of samples for constructing the calibration set in the multivariate regression model and has superior predictive performance compared with the existing classic sample-selection KS strategies.
KeywordConsensus Selection calibration Set multivariate Regression Model partial Least Squares (Pls) derivative Spectra
WOS HeadingsScience & Technology ; Technology ; Physical Sciences
DOI10.1016/j.chemolab.2016.05.007
WOS KeywordREPRESENTATIVE SUBSET-SELECTION ; NEAR-INFRARED SPECTRA ; MULTIVARIATE CALIBRATION ; DIFFERENTIATION ; STANDARDIZATION ; VALIDATION ; REGRESSION ; VARIABLES ; MODELS ; NIR
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(31170956) ; Natural Science Foundation of Hebei(F2016501138 ; Fundamental Research Funds for the Central Universities(N142304006) ; F2014501127)
WOS Research AreaAutomation & Control Systems ; Chemistry ; Computer Science ; Instruments & Instrumentation ; Mathematics
WOS SubjectAutomation & Control Systems ; Chemistry, Analytical ; Computer Science, Artificial Intelligence ; Instruments & Instrumentation ; Mathematics, Interdisciplinary Applications ; Statistics & Probability
WOS IDWOS:000380415100002
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12172
Collection智能制造技术与系统研究中心_多维数据分析
Corresponding AuthorZhigang Li
Recommended Citation
GB/T 7714
Li, Zhigang,Liu, Jiemin,Shan, Peng,et al. Strategy for constructing calibration sets based on a derivative spectra information space consensus[J]. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS,2016,156(156):7–13.
APA Li, Zhigang,Liu, Jiemin,Shan, Peng,et al.,&Zhigang Li.(2016).Strategy for constructing calibration sets based on a derivative spectra information space consensus.CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS,156(156),7–13.
MLA Li, Zhigang,et al."Strategy for constructing calibration sets based on a derivative spectra information space consensus".CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 156.156(2016):7–13.
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