| abstract |
The invention discloses a lake/silo eutrophication prediction method based on an artificial intelligence algorithm, comprising the following steps: 1) collecting data to establish a database; 2) building a radial basis function network: the first layer is the input layer; the second layer is the hidden layer, and the output of the hidden nodes is the basis function; the third layer is the output layer, and each output node is connected to all hidden nodes; the output results of the output layer of the radial basis function network include: chlorophyll a concentration; Input indicators include: nitrogen and phosphorus nutrient concentration, chemical oxygen demand, water temperature, turbidity, electrical conductivity, dissolved oxygen concentration; 3) radial basis function network learning; 4) radial basis function network prediction function test. The method overcomes the problems of difficult parameter calibration and relatively long time-consuming in the traditional method using the hydrodynamic water ecological mathematical model, and also stably improves the prediction and calculation accuracy of lake (reservoir) eutrophication. |