Local Strategy Combined with a Wavelength Selection Method for Multivariate Calibration
One of the essential factors influencing the prediction accuracy of multivariate calibration models is the quality of the calibration data. A local regression strategy, together with a wavelength selection approach, is proposed to build the multivariate calibration models based on partial least squa...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2016-06-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/16/6/827 |
| _version_ | 1817990583294099456 |
|---|---|
| author | Haitao Chang Lianqing Zhu Xiaoping Lou Xiaochen Meng Yangkuan Guo Zhongyu Wang |
| author_facet | Haitao Chang Lianqing Zhu Xiaoping Lou Xiaochen Meng Yangkuan Guo Zhongyu Wang |
| author_sort | Haitao Chang |
| collection | DOAJ |
| description | One of the essential factors influencing the prediction accuracy of multivariate calibration models is the quality of the calibration data. A local regression strategy, together with a wavelength selection approach, is proposed to build the multivariate calibration models based on partial least squares regression. The local algorithm is applied to create a calibration set of spectra similar to the spectrum of an unknown sample; the synthetic degree of grey relation coefficient is used to evaluate the similarity. A wavelength selection method based on simple-to-use interactive self-modeling mixture analysis minimizes the influence of noisy variables, and the most informative variables of the most similar samples are selected to build the multivariate calibration model based on partial least squares regression. To validate the performance of the proposed method, ultraviolet-visible absorbance spectra of mixed solutions of food coloring analytes in a concentration range of 20–200 µg/mL is measured. Experimental results show that the proposed method can not only enhance the prediction accuracy of the calibration model, but also greatly reduce its complexity. |
| first_indexed | 2024-04-14T01:02:01Z |
| format | Article |
| id | doaj.art-0109dd73b97d4f309431506b4cbda4f9 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T01:02:01Z |
| publishDate | 2016-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-0109dd73b97d4f309431506b4cbda4f92022-12-22T02:21:23ZengMDPI AGSensors1424-82202016-06-0116682710.3390/s16060827s16060827Local Strategy Combined with a Wavelength Selection Method for Multivariate CalibrationHaitao Chang0Lianqing Zhu1Xiaoping Lou2Xiaochen Meng3Yangkuan Guo4Zhongyu Wang5School of Instrumentation Science & Opto-Electronics Engineering, Beihang University, Beijing 100191, ChinaBeijing Key Laboratory for Optoelectronic Measurement Technology, Beijing Information Science & Technology University, Beijing 100192, ChinaBeijing Key Laboratory for Optoelectronic Measurement Technology, Beijing Information Science & Technology University, Beijing 100192, ChinaBeijing Key Laboratory for Optoelectronic Measurement Technology, Beijing Information Science & Technology University, Beijing 100192, ChinaBeijing Key Laboratory for Optoelectronic Measurement Technology, Beijing Information Science & Technology University, Beijing 100192, ChinaSchool of Instrumentation Science & Opto-Electronics Engineering, Beihang University, Beijing 100191, ChinaOne of the essential factors influencing the prediction accuracy of multivariate calibration models is the quality of the calibration data. A local regression strategy, together with a wavelength selection approach, is proposed to build the multivariate calibration models based on partial least squares regression. The local algorithm is applied to create a calibration set of spectra similar to the spectrum of an unknown sample; the synthetic degree of grey relation coefficient is used to evaluate the similarity. A wavelength selection method based on simple-to-use interactive self-modeling mixture analysis minimizes the influence of noisy variables, and the most informative variables of the most similar samples are selected to build the multivariate calibration model based on partial least squares regression. To validate the performance of the proposed method, ultraviolet-visible absorbance spectra of mixed solutions of food coloring analytes in a concentration range of 20–200 µg/mL is measured. Experimental results show that the proposed method can not only enhance the prediction accuracy of the calibration model, but also greatly reduce its complexity.http://www.mdpi.com/1424-8220/16/6/827partial least squares regressionwavelength selectionmultivariate calibrationultraviolet-visible absorbance spectralocal algorithm |
| spellingShingle | Haitao Chang Lianqing Zhu Xiaoping Lou Xiaochen Meng Yangkuan Guo Zhongyu Wang Local Strategy Combined with a Wavelength Selection Method for Multivariate Calibration Sensors partial least squares regression wavelength selection multivariate calibration ultraviolet-visible absorbance spectra local algorithm |
| title | Local Strategy Combined with a Wavelength Selection Method for Multivariate Calibration |
| title_full | Local Strategy Combined with a Wavelength Selection Method for Multivariate Calibration |
| title_fullStr | Local Strategy Combined with a Wavelength Selection Method for Multivariate Calibration |
| title_full_unstemmed | Local Strategy Combined with a Wavelength Selection Method for Multivariate Calibration |
| title_short | Local Strategy Combined with a Wavelength Selection Method for Multivariate Calibration |
| title_sort | local strategy combined with a wavelength selection method for multivariate calibration |
| topic | partial least squares regression wavelength selection multivariate calibration ultraviolet-visible absorbance spectra local algorithm |
| url | http://www.mdpi.com/1424-8220/16/6/827 |
| work_keys_str_mv | AT haitaochang localstrategycombinedwithawavelengthselectionmethodformultivariatecalibration AT lianqingzhu localstrategycombinedwithawavelengthselectionmethodformultivariatecalibration AT xiaopinglou localstrategycombinedwithawavelengthselectionmethodformultivariatecalibration AT xiaochenmeng localstrategycombinedwithawavelengthselectionmethodformultivariatecalibration AT yangkuanguo localstrategycombinedwithawavelengthselectionmethodformultivariatecalibration AT zhongyuwang localstrategycombinedwithawavelengthselectionmethodformultivariatecalibration |