Feasibility of On-line Measurement of Sewage Components Using the UV Absorbance and the Neural Network
Abstract The objective of this study was to test the feasibility of a new method to improve the accuracy in the estimation of sewage components. Adding to the regression of sewage components with UV (ultraviolet) absorbance values, a proposed method considered an unclear but existing relationship am...
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| Autor*in: |
Jeong, Hyeong-Seok [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2007 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media B.V. 2007 |
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| Übergeordnetes Werk: |
Enthalten in: Environmental monitoring and assessment - Springer Netherlands, 1981, 133(2007), 1-3 vom: 08. Feb., Seite 15-24 |
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| Übergeordnetes Werk: |
volume:133 ; year:2007 ; number:1-3 ; day:08 ; month:02 ; pages:15-24 |
| Links: |
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| DOI / URN: |
10.1007/s10661-006-9555-4 |
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OLC2073726437 |
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| 520 | |a Abstract The objective of this study was to test the feasibility of a new method to improve the accuracy in the estimation of sewage components. Adding to the regression of sewage components with UV (ultraviolet) absorbance values, a proposed method considered an unclear but existing relationship among characteristic of sewage production. Sewage production showed very defined profiles due to the daily human activities. So the main idea was the combination of measuring the UV absorbance values and analyzing the characteristics of the sewage production. For this purpose, 446 sewage samples taken at every 2-h interval for 51 days at a wastewater treatment plant were statistically analyzed using neural network (NN). NN was trained with 350 data sets (about 29 days) of UV absorbance values, flow rate and time. And as a result, it could predict 96 data (12 days) as a validation, indicating that estimation accuracies were improved to higher level than those of the linear regressions. The proposed method could estimate concentrations of total nitrogen (TN) and total phosphate (TP) within practical accuracies as well as total suspended solid. | ||
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10.1007/s10661-006-9555-4 doi (DE-627)OLC2073726437 (DE-He213)s10661-006-9555-4-p DE-627 ger DE-627 rakwb eng 333.7 VZ Jeong, Hyeong-Seok verfasserin aut Feasibility of On-line Measurement of Sewage Components Using the UV Absorbance and the Neural Network 2007 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media B.V. 2007 Abstract The objective of this study was to test the feasibility of a new method to improve the accuracy in the estimation of sewage components. Adding to the regression of sewage components with UV (ultraviolet) absorbance values, a proposed method considered an unclear but existing relationship among characteristic of sewage production. Sewage production showed very defined profiles due to the daily human activities. So the main idea was the combination of measuring the UV absorbance values and analyzing the characteristics of the sewage production. For this purpose, 446 sewage samples taken at every 2-h interval for 51 days at a wastewater treatment plant were statistically analyzed using neural network (NN). NN was trained with 350 data sets (about 29 days) of UV absorbance values, flow rate and time. And as a result, it could predict 96 data (12 days) as a validation, indicating that estimation accuracies were improved to higher level than those of the linear regressions. The proposed method could estimate concentrations of total nitrogen (TN) and total phosphate (TP) within practical accuracies as well as total suspended solid. Sewage UV absorbance On-line measurement Neural network Lee, Sang-Hyung aut Shin, Hang-Sik aut Enthalten in Environmental monitoring and assessment Springer Netherlands, 1981 133(2007), 1-3 vom: 08. Feb., Seite 15-24 (DE-627)130549649 (DE-600)782621-7 (DE-576)476125413 0167-6369 nnns volume:133 year:2007 number:1-3 day:08 month:02 pages:15-24 https://doi.org/10.1007/s10661-006-9555-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-FOR SSG-OLC-IBL GBV_ILN_22 GBV_ILN_70 GBV_ILN_4012 GBV_ILN_4219 AR 133 2007 1-3 08 02 15-24 |
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10.1007/s10661-006-9555-4 doi (DE-627)OLC2073726437 (DE-He213)s10661-006-9555-4-p DE-627 ger DE-627 rakwb eng 333.7 VZ Jeong, Hyeong-Seok verfasserin aut Feasibility of On-line Measurement of Sewage Components Using the UV Absorbance and the Neural Network 2007 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media B.V. 2007 Abstract The objective of this study was to test the feasibility of a new method to improve the accuracy in the estimation of sewage components. Adding to the regression of sewage components with UV (ultraviolet) absorbance values, a proposed method considered an unclear but existing relationship among characteristic of sewage production. Sewage production showed very defined profiles due to the daily human activities. So the main idea was the combination of measuring the UV absorbance values and analyzing the characteristics of the sewage production. For this purpose, 446 sewage samples taken at every 2-h interval for 51 days at a wastewater treatment plant were statistically analyzed using neural network (NN). NN was trained with 350 data sets (about 29 days) of UV absorbance values, flow rate and time. And as a result, it could predict 96 data (12 days) as a validation, indicating that estimation accuracies were improved to higher level than those of the linear regressions. The proposed method could estimate concentrations of total nitrogen (TN) and total phosphate (TP) within practical accuracies as well as total suspended solid. Sewage UV absorbance On-line measurement Neural network Lee, Sang-Hyung aut Shin, Hang-Sik aut Enthalten in Environmental monitoring and assessment Springer Netherlands, 1981 133(2007), 1-3 vom: 08. Feb., Seite 15-24 (DE-627)130549649 (DE-600)782621-7 (DE-576)476125413 0167-6369 nnns volume:133 year:2007 number:1-3 day:08 month:02 pages:15-24 https://doi.org/10.1007/s10661-006-9555-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-FOR SSG-OLC-IBL GBV_ILN_22 GBV_ILN_70 GBV_ILN_4012 GBV_ILN_4219 AR 133 2007 1-3 08 02 15-24 |
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10.1007/s10661-006-9555-4 doi (DE-627)OLC2073726437 (DE-He213)s10661-006-9555-4-p DE-627 ger DE-627 rakwb eng 333.7 VZ Jeong, Hyeong-Seok verfasserin aut Feasibility of On-line Measurement of Sewage Components Using the UV Absorbance and the Neural Network 2007 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media B.V. 2007 Abstract The objective of this study was to test the feasibility of a new method to improve the accuracy in the estimation of sewage components. Adding to the regression of sewage components with UV (ultraviolet) absorbance values, a proposed method considered an unclear but existing relationship among characteristic of sewage production. Sewage production showed very defined profiles due to the daily human activities. So the main idea was the combination of measuring the UV absorbance values and analyzing the characteristics of the sewage production. For this purpose, 446 sewage samples taken at every 2-h interval for 51 days at a wastewater treatment plant were statistically analyzed using neural network (NN). NN was trained with 350 data sets (about 29 days) of UV absorbance values, flow rate and time. And as a result, it could predict 96 data (12 days) as a validation, indicating that estimation accuracies were improved to higher level than those of the linear regressions. The proposed method could estimate concentrations of total nitrogen (TN) and total phosphate (TP) within practical accuracies as well as total suspended solid. Sewage UV absorbance On-line measurement Neural network Lee, Sang-Hyung aut Shin, Hang-Sik aut Enthalten in Environmental monitoring and assessment Springer Netherlands, 1981 133(2007), 1-3 vom: 08. Feb., Seite 15-24 (DE-627)130549649 (DE-600)782621-7 (DE-576)476125413 0167-6369 nnns volume:133 year:2007 number:1-3 day:08 month:02 pages:15-24 https://doi.org/10.1007/s10661-006-9555-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-FOR SSG-OLC-IBL GBV_ILN_22 GBV_ILN_70 GBV_ILN_4012 GBV_ILN_4219 AR 133 2007 1-3 08 02 15-24 |
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10.1007/s10661-006-9555-4 doi (DE-627)OLC2073726437 (DE-He213)s10661-006-9555-4-p DE-627 ger DE-627 rakwb eng 333.7 VZ Jeong, Hyeong-Seok verfasserin aut Feasibility of On-line Measurement of Sewage Components Using the UV Absorbance and the Neural Network 2007 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media B.V. 2007 Abstract The objective of this study was to test the feasibility of a new method to improve the accuracy in the estimation of sewage components. Adding to the regression of sewage components with UV (ultraviolet) absorbance values, a proposed method considered an unclear but existing relationship among characteristic of sewage production. Sewage production showed very defined profiles due to the daily human activities. So the main idea was the combination of measuring the UV absorbance values and analyzing the characteristics of the sewage production. For this purpose, 446 sewage samples taken at every 2-h interval for 51 days at a wastewater treatment plant were statistically analyzed using neural network (NN). NN was trained with 350 data sets (about 29 days) of UV absorbance values, flow rate and time. And as a result, it could predict 96 data (12 days) as a validation, indicating that estimation accuracies were improved to higher level than those of the linear regressions. The proposed method could estimate concentrations of total nitrogen (TN) and total phosphate (TP) within practical accuracies as well as total suspended solid. Sewage UV absorbance On-line measurement Neural network Lee, Sang-Hyung aut Shin, Hang-Sik aut Enthalten in Environmental monitoring and assessment Springer Netherlands, 1981 133(2007), 1-3 vom: 08. Feb., Seite 15-24 (DE-627)130549649 (DE-600)782621-7 (DE-576)476125413 0167-6369 nnns volume:133 year:2007 number:1-3 day:08 month:02 pages:15-24 https://doi.org/10.1007/s10661-006-9555-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-FOR SSG-OLC-IBL GBV_ILN_22 GBV_ILN_70 GBV_ILN_4012 GBV_ILN_4219 AR 133 2007 1-3 08 02 15-24 |
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10.1007/s10661-006-9555-4 doi (DE-627)OLC2073726437 (DE-He213)s10661-006-9555-4-p DE-627 ger DE-627 rakwb eng 333.7 VZ Jeong, Hyeong-Seok verfasserin aut Feasibility of On-line Measurement of Sewage Components Using the UV Absorbance and the Neural Network 2007 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media B.V. 2007 Abstract The objective of this study was to test the feasibility of a new method to improve the accuracy in the estimation of sewage components. Adding to the regression of sewage components with UV (ultraviolet) absorbance values, a proposed method considered an unclear but existing relationship among characteristic of sewage production. Sewage production showed very defined profiles due to the daily human activities. So the main idea was the combination of measuring the UV absorbance values and analyzing the characteristics of the sewage production. For this purpose, 446 sewage samples taken at every 2-h interval for 51 days at a wastewater treatment plant were statistically analyzed using neural network (NN). NN was trained with 350 data sets (about 29 days) of UV absorbance values, flow rate and time. And as a result, it could predict 96 data (12 days) as a validation, indicating that estimation accuracies were improved to higher level than those of the linear regressions. The proposed method could estimate concentrations of total nitrogen (TN) and total phosphate (TP) within practical accuracies as well as total suspended solid. Sewage UV absorbance On-line measurement Neural network Lee, Sang-Hyung aut Shin, Hang-Sik aut Enthalten in Environmental monitoring and assessment Springer Netherlands, 1981 133(2007), 1-3 vom: 08. Feb., Seite 15-24 (DE-627)130549649 (DE-600)782621-7 (DE-576)476125413 0167-6369 nnns volume:133 year:2007 number:1-3 day:08 month:02 pages:15-24 https://doi.org/10.1007/s10661-006-9555-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-FOR SSG-OLC-IBL GBV_ILN_22 GBV_ILN_70 GBV_ILN_4012 GBV_ILN_4219 AR 133 2007 1-3 08 02 15-24 |
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Abstract The objective of this study was to test the feasibility of a new method to improve the accuracy in the estimation of sewage components. Adding to the regression of sewage components with UV (ultraviolet) absorbance values, a proposed method considered an unclear but existing relationship among characteristic of sewage production. Sewage production showed very defined profiles due to the daily human activities. So the main idea was the combination of measuring the UV absorbance values and analyzing the characteristics of the sewage production. For this purpose, 446 sewage samples taken at every 2-h interval for 51 days at a wastewater treatment plant were statistically analyzed using neural network (NN). NN was trained with 350 data sets (about 29 days) of UV absorbance values, flow rate and time. And as a result, it could predict 96 data (12 days) as a validation, indicating that estimation accuracies were improved to higher level than those of the linear regressions. The proposed method could estimate concentrations of total nitrogen (TN) and total phosphate (TP) within practical accuracies as well as total suspended solid. © Springer Science+Business Media B.V. 2007 |
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Abstract The objective of this study was to test the feasibility of a new method to improve the accuracy in the estimation of sewage components. Adding to the regression of sewage components with UV (ultraviolet) absorbance values, a proposed method considered an unclear but existing relationship among characteristic of sewage production. Sewage production showed very defined profiles due to the daily human activities. So the main idea was the combination of measuring the UV absorbance values and analyzing the characteristics of the sewage production. For this purpose, 446 sewage samples taken at every 2-h interval for 51 days at a wastewater treatment plant were statistically analyzed using neural network (NN). NN was trained with 350 data sets (about 29 days) of UV absorbance values, flow rate and time. And as a result, it could predict 96 data (12 days) as a validation, indicating that estimation accuracies were improved to higher level than those of the linear regressions. The proposed method could estimate concentrations of total nitrogen (TN) and total phosphate (TP) within practical accuracies as well as total suspended solid. © Springer Science+Business Media B.V. 2007 |
| abstract_unstemmed |
Abstract The objective of this study was to test the feasibility of a new method to improve the accuracy in the estimation of sewage components. Adding to the regression of sewage components with UV (ultraviolet) absorbance values, a proposed method considered an unclear but existing relationship among characteristic of sewage production. Sewage production showed very defined profiles due to the daily human activities. So the main idea was the combination of measuring the UV absorbance values and analyzing the characteristics of the sewage production. For this purpose, 446 sewage samples taken at every 2-h interval for 51 days at a wastewater treatment plant were statistically analyzed using neural network (NN). NN was trained with 350 data sets (about 29 days) of UV absorbance values, flow rate and time. And as a result, it could predict 96 data (12 days) as a validation, indicating that estimation accuracies were improved to higher level than those of the linear regressions. The proposed method could estimate concentrations of total nitrogen (TN) and total phosphate (TP) within practical accuracies as well as total suspended solid. © Springer Science+Business Media B.V. 2007 |
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Feasibility of On-line Measurement of Sewage Components Using the UV Absorbance and the Neural Network |
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