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Neural networks are increasingly used in the study of deformation control dam based on its self-organization, adaptive, self-learning, associative memory, a high degree of fault-tolerant, parallel processing abilities, a high degree of non-linear mapping capability, as well as linear dynamic characteristics. In this paper combines former research achievements, summarize and analyze the application...
In view of the complexity of Back Analysis of rock-fill material parameter, this paper uses genetic algorithm optimization BP neural network weights and threshold, simulated finite element calculation of rockfill dam by genetic neural network, combined with the theory of particle swarm optimization algorithm, and has realized inverse analysis of particle swarm optimization and genetic neural network...
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