Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4403836 | Procedia Environmental Sciences | 2010 | 9 Pages |
Abstract
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.
Related Topics
Life Sciences
Environmental Science
Ecology