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For: Milanez KDTM, Araújo Nóbrega TC, Silva Nascimento D, Galvão RKH, Pontes MJC. Selection of robust variables for transfer of classification models employing the successive projections algorithm. Analytica Chimica Acta 2017;984:76-85. [DOI: 10.1016/j.aca.2017.07.037] [Cited by in Crossref: 14] [Cited by in F6Publishing: 5] [Article Influence: 2.8] [Reference Citation Analysis]
Number Citing Articles
1 Liu F, Shen T, Kong W, Peng J, Zhang C, Song K, Wang W, Zhang C, He Y. Quantitative Analysis of Cadmium in Tobacco Roots Using Laser-Induced Breakdown Spectroscopy With Variable Index and Chemometrics. Front Plant Sci 2018;9:1316. [PMID: 30271417 DOI: 10.3389/fpls.2018.01316] [Cited by in Crossref: 14] [Cited by in F6Publishing: 7] [Article Influence: 3.5] [Reference Citation Analysis]
2 Shi J, Wang Y, Liu C, Li Z, Huang X, Guo Z, Zhang X, Zhang D, Zou X. Application of spectral features for separating homochromatic foreign matter from mixed congee. Food Chem X 2021;11:100128. [PMID: 34485896 DOI: 10.1016/j.fochx.2021.100128] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Kalivas JH, Lemos T. Automatic food and beverage authentication and adulteration detection by classification hybrid fusion. Journal of Chemometrics. [DOI: 10.1002/cem.3371] [Reference Citation Analysis]
4 Duan F, Fu X, Jiang J, Huang T, Ma L, Zhang C. Automatic variable selection method and a comparison for quantitative analysis in laser-induced breakdown spectroscopy. Spectrochimica Acta Part B: Atomic Spectroscopy 2018;143:12-7. [DOI: 10.1016/j.sab.2018.02.010] [Cited by in Crossref: 18] [Cited by in F6Publishing: 6] [Article Influence: 4.5] [Reference Citation Analysis]
5 Zhang J, Cui X, Cai W, Shao X. A variable importance criterion for variable selection in near-infrared spectral analysis. Sci China Chem 2019;62:271-9. [DOI: 10.1007/s11426-018-9368-9] [Cited by in Crossref: 6] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]
6 Pasquini C. Near infrared spectroscopy: A mature analytical technique with new perspectives – A review. Analytica Chimica Acta 2018;1026:8-36. [DOI: 10.1016/j.aca.2018.04.004] [Cited by in Crossref: 302] [Cited by in F6Publishing: 126] [Article Influence: 75.5] [Reference Citation Analysis]
7 Yu H, Wang X, Shen F, Long J, Du W. Novel automatic model construction method for the rapid characterization of petroleum properties from near-infrared spectroscopy. Fuel 2022;316:123101. [DOI: 10.1016/j.fuel.2021.123101] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
8 Luo N, Han P, Wang S, Wang D, Zhao C. Near-Infrared Spectroscopy Analytical Model Using Ensemble Partial Least Squares Regression. Analytical Letters 2019;52:1732-56. [DOI: 10.1080/00032719.2019.1568447] [Cited by in Crossref: 1] [Article Influence: 0.3] [Reference Citation Analysis]
9 Solórzano A, Rodríguez-pérez R, Padilla M, Graunke T, Fernandez L, Marco S, Fonollosa J. Multi-unit calibration rejects inherent device variability of chemical sensor arrays. Sensors and Actuators B: Chemical 2018;265:142-54. [DOI: 10.1016/j.snb.2018.02.188] [Cited by in Crossref: 17] [Cited by in F6Publishing: 2] [Article Influence: 4.3] [Reference Citation Analysis]
10 Liu N, Qiao L, Xing Z, Li M, Sun H, Zhang J, Zhang Y. Detection of chlorophyll content in growth potato based on spectral variable analysis. Spectroscopy Letters 2020;53:476-88. [DOI: 10.1080/00387010.2020.1772827] [Cited by in Crossref: 4] [Article Influence: 2.0] [Reference Citation Analysis]
11 Shan P, Li Z, Wang Q, He Z, Wang S, Zhao Y, Wu Z, Peng S. Self-organizing maps-based generalized feature set selection for model adaption without reference data for batch process. Anal Chim Acta 2021;1188:339205. [PMID: 34794558 DOI: 10.1016/j.aca.2021.339205] [Reference Citation Analysis]
12 Zhang F, Du K, Guo L, Huo Y, He K, Shan B. Progress, problems, and potential of technology for measuring solution concentration in crystallization processes. Measurement 2022;187:110328. [DOI: 10.1016/j.measurement.2021.110328] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
13 Pontes AS, Araújo A, Marinho W, Gonçalves Dias Diniz PH, Araújo Gomes A, Goicoechea HC, Silva EC, Araújo MC. Ant colony optimization for variable selection in discriminant linear analysis. Journal of Chemometrics 2020;34. [DOI: 10.1002/cem.3292] [Reference Citation Analysis]
14 Zhang J, Xiong Y, Min S. A new hybrid filter/wrapper algorithm for feature selection in classification. Analytica Chimica Acta 2019;1080:43-54. [DOI: 10.1016/j.aca.2019.06.054] [Cited by in Crossref: 18] [Cited by in F6Publishing: 4] [Article Influence: 6.0] [Reference Citation Analysis]
15 Tang W, Wang N, Zhao R, Li M, Sun H, An L, Qiao L. Chlorophyll detector development based on snapshot-mosaic multispectral image sensing and field wheat canopy processing. Computers and Electronics in Agriculture 2022;197:106999. [DOI: 10.1016/j.compag.2022.106999] [Reference Citation Analysis]
16 Ruan F, Hou L, Zhang T, Li H. A novel hybrid filter/wrapper method for feature selection in archaeological ceramics classification by laser-induced breakdown spectroscopy. Analyst 2021;146:1023-31. [PMID: 33300506 DOI: 10.1039/d0an02045a] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
17 Li Q, Huang Y, Tian K. Optimal modeling pattern of variables selection on analog complex using UVE-PLS regression. IOPSciNotes 2020;1:014201. [DOI: 10.1088/2633-1357/ab8d46] [Reference Citation Analysis]