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A hybrid neural network model for cyanobacteria bloom in Dianehi Lake

机译:浅藻植物的混合神经网络模型

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Cyanobacteria bloom predicting is an important part of water quality management in eutrophic lakes or reservoirs. This paper developed a hybrid model consisting of back-propagation neural network and rough decision to predict the cyanobacteria bloom in Dianchi Lake using weather conditions. The rough reduct could be used to select essential factors for the neural network. The training efficacy of the hybrid model was more effective than that of neural network model merely. And compared to other models, the predicting accuracy of the hybrid model was also obviously improved.
机译:蓝藻绽放预测是富营养化湖泊或水库水质管理的重要组成部分。本文开发了一种混合模型,包括使用天气状况来预测滇池绽放的粗糙决定的混合模型。粗糙度减少可用于为神经网络选择基本因素。混合模型的训练功效仅仅比神经网络模型更有效。与其他模型相比,混合模型的预测精度也显然得到了改善。

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