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- W2769659968 abstract "Water pollution has been increasing quickly and complexly for recent years. Water quality forecast to provide prompt and timely information on water pollution is very necessary. In this study, the aim of the study was to compare capability of water quality forecast by the multilayer perceptron neural network method and the grey theory method that emphasized rapid predictability and accuracy, contributing to improving the efficiency of water quality forecast. The data were collected from 23 monitoring stations of Dong Nai river from 2010 to 2014 in Dong Nai and Binh Duong Department of Natural Resources and Environment for forecasting the water quality index. The results showed that both methods had good performance of water quality forecast. The water quality index forecasted by the multilayer perceptron neural network model showed higher accuracy (RMSE = 2.88, R2 = 0.987 and P = 0) than that forecasted by the grey theory model (RMSE = 7.84, R2 = 0.879 and P = 0)." @default.
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- W2769659968 date "2017-01-01" @default.
- W2769659968 modified "2023-09-23" @default.
- W2769659968 title "So sánh khả năng dự đoán chất lượng nước sông Đồng Nai bằng mạng nơ ron nhân tạo và lý thuyết xám" @default.
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- W2769659968 doi "https://doi.org/10.22144/ctu.jsi.2017.038" @default.
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