Drinking water safety is directly related to public health. Urban water sources must maintain people’s life and social stability in the event of major accidents. In building a welfare society, the realization of social harmony is the basic guarantee for urban water supply, emergency preparedness, social stability and sustainable development of the city. The urban water cycle is managed by a large amount of cooling water. However, with the current intensive water supply, the water quality has gradually deteriorated. In particular, surface water contains various pollutants, including inorganic matter, organic matter, dissolved matter and suspended matter, which have a certain impact on metal or non-metallic substances in the system. On the one hand, scale or dirt is formed on the surface of the heat exchanger, which reduces the overall efficiency of the system and increases the resistance. On the other hand, it directly corrodes the metal materials of the cooling water system, which even affects the quality of the condensate water, and threatens the safe operation of the boiler. Therefore, the prevention of the pollution of urban circulating water system is a very important work. Semi-supervised learning and Bayesian algorithm have played an excellent role in water pollution control. This paper applied this algorithm to the construction of urban water source circulating water pollution prevention system. Finally, it was concluded that the removal rate of suspended solids could be greatly improved by adopting the urban water source circulating water pollution prevention system. The elimination rate of total nitrogen was 31.4% higher than that before using the urban water source circulating water pollution prevention system, thus effectively preventing and controlling water pollution.

Jungho Ahn. Construction of Urban Water Source Circulating Water Pollution Prevention System Based on Semi-supervised Learning and Bayesian Algorithm. Water Pollution Prevention and Control Project (2021), Vol. 2, Issue 2: 22-32. https://doi.org/10.38007/WPPCP.2021.020203.

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