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10 July 2020 Application of Back Propagation (BP) Neural Network in Water Quality Assessment: A Case Study of Ashi River Basin
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Abstract

Wang, H., 2020. Application of back propagation (BP) neural network in water quality assessment: A case study of Ashi River Basin. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 377–380. Coconut Creek (Florida), ISSN 0749-0208.

The artificial neural network (ANN) theory and method was adopted to establish a back propagation (BP) neural network model for the assessment of water quality. Considering the water quality in the Ashi River basin as an example, a comparative analysis between the obtained results and the results from the Nemerow index method shows that the BP neural network model is applicable to evaluate the river basin water quality, and the model has a good reliability. By simulating the human brain in the thought process and analysis mode, the accuracy of water quality assessment is greatly improved, which means that the model can provide a reliable basis for assessing the water quality of the river basin.

©Coastal Education and Research Foundation, Inc. 2020
Hugen Wang "Application of Back Propagation (BP) Neural Network in Water Quality Assessment: A Case Study of Ashi River Basin," Journal of Coastal Research 106(sp1), 377-380, (10 July 2020). https://doi.org/10.2112/SI106-087.1
Received: 20 December 2019; Accepted: 25 January 2020; Published: 10 July 2020
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