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Lake and reservoir alga bloom's eruption is resulted by multiple factors, and its formation mechanism is rather complicated. A simulation of this eruption has been conducted in sunshine-room laboratory, then analysis the primary factor influencing the alga growth by rough set theory, through mutation theory to determine the critical factors of eruption. On this basis, the peak mutation model featured...
On the basis of studying the mechanism of water bloom, one kind of gray-BP artificial neural network forecasting method is proposed in the paper. The gray theory was used to obtain preliminary forecast of the occurrence trend of water bloom, combined with neural network to implement error compensation for the forecast result. Compared with BP, this method can predict chlorophyll change trend more...
Analyzing the characters of water-bloom eruption, one effective model on weightings attribute of forecasting water-bloom based on D-S evidence theory has been proposed. After pre-treating forecast index data, sets up water -bloom short-time forecast model based on neural network, which improves forecast precision of water-bloom, through simulation and testing, the result shows its affectivity and...
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