[1] Han Z Z, Wan J H, Liu K W. Model optimization in prediction of gas octane value by NIR[J]. Chinese Journal of Analysis Laboratory, 34, 1268-1271(2015).

[2] Ouyang A G, Zhang Y, Tang T Y et al. Analysis of methanol/ethanol diesel identification and content determination based on the mid-infrared spectra[J]. Laser & Optoelectronics Progress, 54, 093003(2017).

[3] Ding H Y, Huang R H, Wang Z W et al. Simulations and applications of bubble/dew curve for different ethanol-gasoline blends[J]. Journal of Huazhong University of Science and Technology(Natural Science Edition), 40, 113-116(2012).

[4] Liu Y D, Wu M M, Sun X D et al. Simultaneous detection of surface deficiency and soluble solids content for Amygdalus persica by online visible-near infrared transmittance spectroscopy[J]. Transactions of the Chinese Society of Agricultural Engineering, 32, 289-295(2016).

[5] Dan T N, Dai L K. Spectral wavelength selection based on PLS projection analysis[J]. Spectroscopy and Spectral Analysis, 29, 351-354(2009).

[6] Zu Q, Zhang S F, Cao Y et al. Research on identification of cabbages and weeds combining spectral imaging technology and SAM taxonomy[J]. Spectroscopy and Spectral Analysis, 35, 479-485(2015).

[7] Ouyang A G, Tang T Y, Zhou X et al. Methanol content determination in methanol diesel with mid infrared spectroscopy analysis using least square support vector machine[J]. Chinese Journal of Luminescence, 37, 1253-1258(2016).

[8] Ouyang A G, Liu J. On quantitative analysis of methanol content in methanol gasoline by near infrared and Raman spectroscopy[J]. Journal of Southwest China Normal University(Natural Science Edition), 37, 98-101(2012).

[9] Yao J, Dai L K, Lin Y L. Determination of methanol ratio in methanol gasoline based on Raman characteristic peaks[J]. The Journal of Light Scattering, 25, 59-65(2013).

[10] Li Y R, Sun R Q, Wang Y M. Determination of methanol in methanol gasoline for motor vehicles by gas chromatography[J]. Modern Chemical Industry, 33, 113-115(2013).

[11] Hua H N, Xue K, Shi B W et al[J]. A real-time online detection method for the methanol content in vehicular methanol gasoline Automobile Parts, 2016, 74-76.

[12] Cai W S, Li Y K, Shao X G. A variable selection method based on uninformative variable elimination for multivariate calibration of near-infrared spectra[J]. Chemometrics and Intelligent Laboratory Systems, 90, 188-194(2008).

[13] Soares S F C, Gomes A A, Araujo M C U et al. . The successive projections algorithm[J]. TrAC Trends in Analytical Chemistry, 42, 84-98(2013).

[14] [14] CerradaM, ZuritaG, CabreraD, et al. Fault diagnosis in spur gears based on genetic algorithm and random forest[J]. MechanicalSystems and SignalProcessing, 2016, 70/71: 87- 103.

[15] Tang G, Huang Y, Tian K D et al. A new spectral variable selection pattern using competitive adaptive reweighted sampling combined with successive projections algorithm[J]. The Analyst, 139, 4894-4902(2014). http://www.ncbi.nlm.nih.gov/pubmed/25078711

[16] Li Q Q, Huang Y, Song X Z et al. Moving window smoothing on the ensemble of competitive adaptive reweighted sampling algorithm[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 214, 129-138(2019).

[17] Yang Y, Jin Y, Wu Y J et al. Application of near infrared spectroscopy combined with competitive adaptive reweighted sampling partial least squares for on-line monitoring of the concentration process of Wangbi tablets[J]. Journal of Near Infrared Spectroscopy, 24, 171-178(2016).

[18] Henseler J, Ringle C M, Sinkovics R R[M]. The use of partial least squares path modeling in international marketing, 20, 277-319(2009).