An Improved-Bagging Model for Water Chemical Oxygen Demand Measurements Using UV-Vis Spectroscopy
The ultraviolet-visible (UV-Vis) spectroscopy measurement method of Chemical Oxygen Demand (COD) in water is a simple physical method that can measure water without secondary pollution from chemical reagents. To solve the problems of low accuracy and insufficient generalization capability of the COD...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9638471/ |
| _version_ | 1819101521370939392 |
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| author | Jingwei Li Sisi Pan Jie Bian Wei Jiang |
| author_facet | Jingwei Li Sisi Pan Jie Bian Wei Jiang |
| author_sort | Jingwei Li |
| collection | DOAJ |
| description | The ultraviolet-visible (UV-Vis) spectroscopy measurement method of Chemical Oxygen Demand (COD) in water is a simple physical method that can measure water without secondary pollution from chemical reagents. To solve the problems of low accuracy and insufficient generalization capability of the COD prediction model, an improved Bagging algorithm is proposed and evaluated in this study. The Improved-Bagging algorithm can reduce model variance and bias concurrently, and improves the accuracy and stability of the traditional Bagging algorithm. Results show that the Improved-Bagging algorithm achieves a better prediction ability on different preprocessed data than the traditional Bagging algorithm. After ensemble empirical mode decomposition based (EEMD-Based) algorithm denoising and stability competitive adaptive reweighted sampling (SCARS) algorithm dimension reduction, Improved-Bagging model achieves the best prediction performance. Its coefficient of determination (R<sup>2</sup>) on the prediction set reached 0.9317, its root mean square error of prediction (RMSEP) reached 5.39 mg/L, and its variance reached 5.53 mg<sup>2</sup>. Results also show that the Improved-Bagging algorithm can accurately measure the COD concentration in water, which lays the foundation for the wide application of spectroscopy to measure water quality parameters. |
| first_indexed | 2024-12-22T01:19:59Z |
| format | Article |
| id | doaj.art-50800d8c3016451ea4b64a1051172bdc |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T01:19:59Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-50800d8c3016451ea4b64a1051172bdc2022-12-21T18:43:45ZengIEEEIEEE Access2169-35362021-01-01916183416184510.1109/ACCESS.2021.31331079638471An Improved-Bagging Model for Water Chemical Oxygen Demand Measurements Using UV-Vis SpectroscopyJingwei Li0https://orcid.org/0000-0002-5770-9980Sisi Pan1https://orcid.org/0000-0001-8740-2368Jie Bian2https://orcid.org/0000-0002-8799-8832Wei Jiang3https://orcid.org/0000-0003-4155-2875College of Electrical, Energy and Power Engineering, Yangzhou University, Yangzhou, ChinaCollege of Electrical, Energy and Power Engineering, Yangzhou University, Yangzhou, ChinaCollege of Electrical, Energy and Power Engineering, Yangzhou University, Yangzhou, ChinaCollege of Electrical, Energy and Power Engineering, Yangzhou University, Yangzhou, ChinaThe ultraviolet-visible (UV-Vis) spectroscopy measurement method of Chemical Oxygen Demand (COD) in water is a simple physical method that can measure water without secondary pollution from chemical reagents. To solve the problems of low accuracy and insufficient generalization capability of the COD prediction model, an improved Bagging algorithm is proposed and evaluated in this study. The Improved-Bagging algorithm can reduce model variance and bias concurrently, and improves the accuracy and stability of the traditional Bagging algorithm. Results show that the Improved-Bagging algorithm achieves a better prediction ability on different preprocessed data than the traditional Bagging algorithm. After ensemble empirical mode decomposition based (EEMD-Based) algorithm denoising and stability competitive adaptive reweighted sampling (SCARS) algorithm dimension reduction, Improved-Bagging model achieves the best prediction performance. Its coefficient of determination (R<sup>2</sup>) on the prediction set reached 0.9317, its root mean square error of prediction (RMSEP) reached 5.39 mg/L, and its variance reached 5.53 mg<sup>2</sup>. Results also show that the Improved-Bagging algorithm can accurately measure the COD concentration in water, which lays the foundation for the wide application of spectroscopy to measure water quality parameters.https://ieeexplore.ieee.org/document/9638471/COD measurementsimproved-bagging modelUV-Vis spectroscopywater |
| spellingShingle | Jingwei Li Sisi Pan Jie Bian Wei Jiang An Improved-Bagging Model for Water Chemical Oxygen Demand Measurements Using UV-Vis Spectroscopy IEEE Access COD measurements improved-bagging model UV-Vis spectroscopy water |
| title | An Improved-Bagging Model for Water Chemical Oxygen Demand Measurements Using UV-Vis Spectroscopy |
| title_full | An Improved-Bagging Model for Water Chemical Oxygen Demand Measurements Using UV-Vis Spectroscopy |
| title_fullStr | An Improved-Bagging Model for Water Chemical Oxygen Demand Measurements Using UV-Vis Spectroscopy |
| title_full_unstemmed | An Improved-Bagging Model for Water Chemical Oxygen Demand Measurements Using UV-Vis Spectroscopy |
| title_short | An Improved-Bagging Model for Water Chemical Oxygen Demand Measurements Using UV-Vis Spectroscopy |
| title_sort | improved bagging model for water chemical oxygen demand measurements using uv vis spectroscopy |
| topic | COD measurements improved-bagging model UV-Vis spectroscopy water |
| url | https://ieeexplore.ieee.org/document/9638471/ |
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