Analysis of Water Environmental Quality Using BP Artificial Neural Network in Weihe River Baoji Segment
The BP artificial neural network model in type 7-5-5 was constructed with the surface water quality standard (GB3838-2002) and the surface water quality items such as BOD5 (5 day biochemical oxygen demand), COD (chemical oxygen demand), permanganate index, fluoride, NH3-N, TP (total phosphorus) and...
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Veröffentlicht in: | Applied Mechanics and Materials 2013-01, Vol.401-403, p.2147-2150 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The BP artificial neural network model in type 7-5-5 was constructed with the surface water quality standard (GB3838-2002) and the surface water quality items such as BOD5 (5 day biochemical oxygen demand), COD (chemical oxygen demand), permanganate index, fluoride, NH3-N, TP (total phosphorus) and TN (total nitrogen), and the water environmental quality evaluation was conducted using the trained BP artificial neural network with the water contamination concentration data in 6 sections of Weihe river Baoji segment in year 2009. Results showed that the water quality were GradeIand GradeII in Lin Jia Cun section and Sheng Li Qiao section, and Grade III in the rest section (Wo Long Si Bridge, Guo Zhen Bridge, Cai Jia Po Bridge and Chang Xing Bridge). |
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ISSN: | 1660-9336 1662-7482 1662-7482 |
DOI: | 10.4028/www.scientific.net/AMM.401-403.2147 |