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Studying on river shoal evolution is a fundamental work in the science of water conservancy, water conservancy projects and waterways planning, designing, engineering feasiblility. First of all, the neural network model for predicting the evolution of shoal in a river is established, through training the neural network to determine the number of hidden layer's neural, thus, a more ration neural network...
Based on the analysis of the factors caused ice flood, the paper selected appropriate forecasting factors, established neural network model of ice forecasting combining genetic algorithm (GA) with Levenberg-Marquardt BP(LMBP) neural network. The GA-LMBP algorithm is to train globally using genetic learning algorithm firstly, then train accurately using LMBP algorithm, overcoming the defects of traditional...
Patterns could be discovered from historical data and can be used to recommend decisions suitable for a typical situation in the past. In this study, the sliding window technique was used to discover flood patterns that relate hydrological data consisting of river water levels and rainfall measurements. Unique flood occurrence patterns were obtained at each location. Based on the discovered flood...
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...
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