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Lake eutrophication and algal bloom is one of the most important environmental problems facing China's lakes, and it is also the focus of lake eutrophication control of the world's attention. The monitoring data on chlorophyll concentration was analyzed every one month, combined with corresponding weather conditions from 2004 to 2006. According to the degree of eutrophication in Taihu Lake, it is divided into five Lakes: heavy eutrophication region V, eutrophication region IV, middle-level eutrophication region III, light eutrophication region II and nutrition region I. Based on fuzzy factor optimization method, the average wind speed, average pressure, average temperature and sunshine hours was selected to discuss the influence mechanism of meteorological factors on the algae bloom in Taihu Lake. Considered the four meteorological factors as the input layer nodes, BP neural network model was applied to build the zoning monitoring and early warning model of blue algae in Taihu Lake.

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