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The monitoring data for water quality of Beijing Beihai between May and October in 2007 have been analyzed with gray correlation. In order to overcome the defects of the traditional method, this way consider the interzone form of the water quality evaluation standard, use centralization dimensionless functions, and combine the integrated nutritional status index with const weight. The thread system...
An intelligent method on short-term prediction on water bloom of BP neural network based on rough set and wavelet analysis is proposed in this paper. This method analyzes factors of effecting the outbreak of water bloom, and these many factors which were processed by reduction method based on rough set were used as input information of the prediction model; after analyzing the main input information...
The outbreak of water-bloom is the result of coactions of water body's physical, chemical, biologic and other progresses. It is very difficult to establish uniform mathematical model to efficiently evaluate and predict the water-bloom because of the water body's biodiversity and nonlinearity. Based on the foundation of research in the mechanism of water-bloom and the main component analysis in rivers...
An intelligent prediction model for water bloom of rivers and lakes based on least squares support vector machine (LSSVM) is proposed, in which main influence factor of outbreak of water bloom is analyzed by rough set theory first, and this model is compared with artificial neural network prediction model. The comparison result indicates: in the aspect of medium-term water bloom prediction in rivers...
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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