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Water quality model is a useful tool to evaluate the future state of river water through evaluation of actual pollution loading or different management options. Based on the human brain physiology research, artificial neural network(ANN), which simulates the structure and mechanism of the human brain, is a kind of dynamic information processing system that eventually achieves certain functions of...
According to lagging state of water quality monitor and the problems of the difficult of water bloom prediction, water bloom remote monitor and prediction system based on BP neural network are proposed in this paper. This system can realize the automatic real-time monitor for the change of water quality and via the prediction by neural network for water bloom; it can provide a kind of efficient and...
Using particle swarm optimization (PSO) to optimize BP neural network model is proposed in this paper. The new model is more quickly and accurate. The basic idea of this model is: Firstly PSO is used to optimize the BP neural network's initialized weights, an optimized result is got; then based on the optimized result the BP neural network is used for further optimization. We can use this model for...
The oriental migratory locust plagues has became a serious problem during the last two decades. Remote sensing techniques can greatly facilitate monitoring locust population dynamics over a large geographic scale. In this paper, a model is presented to estimate leaf area index (LAI) of reed canopy from TM or ETM+ image data firstly. The model classifies the background of reed canopy into soil and...
Using principal component analysis (PCA) and improved fuzzy neural network by PSO to evaluate the success degree in electric power engineering is this paper's innovative points. First we construct the algorithm model which based on PCA and BP neural network improved by PSO. Secondly using PCA to predigest the given index system and then using the relative membership degree processing the date, which...
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