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Several artificial intelligence methods in surface water quality monitoring models

  • 2013-09-01
  • 216.24KB
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Abstract: This paper reviews several artificial intelligence methods for surface water quality prediction models, and specifically explains the principles and characteristics of methods such as BP neural network water quality prediction model, surface water COD grey prediction model, time series prediction method and WASP5 model system. It also proposes the trend of integrating the surface water quality prediction model WASP5 with the GIS system. It is necessary to establish an automatic water quality monitoring system in my country based on the current water quality situation and social development. It also analyzes the methods and feasibility of developing an automatic water quality detection system. [Author Abstract]

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