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In the eutrophication evaluation, the uncertainty of evaluation level is the main problem. This process also refers to many factors which have different effect on result. Multi-dimensional normal cloud is a system model which can describe the uncertainty and fuzzy feature. This model involves the factor weight. In our paper, the weight is determined by AHP, CRITIC and information entropy which are...
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...
It is of great importance to put forward an optimal decision scheme as to the emergency control of water bloom in lake and reservoir, so as to prevent water bloom in time and protect the water environment effectively. Based on in-depth analysis on the emergency control decision model and control method of the water bloom, a fuzzy Bayes decision model on the basis of the comprehensive restrictions...
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...
Main factors which make water bloom engendering in river and lakes is analyzed, and the modeling method of short-time predicting for water bloom based on RBF neural network, including supervise learning method for the center, width and weight of base function in RBF neural network, error-correction algorithm based on gradient descent of RBF, is proposed. The effect which hidden layer of RBF brings...
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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