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Models of reservoir regulation based on RBF neural networks

Reservoir regulation is a very complicated problem with much nonlinear relation. The traditional way of reservoir regulation cannot meet the demands of production. In this paper, a new models of reservoir regulation based on RBF neural network is presented. The historical datum of reservoir regulation is used to train RBF neural network in order to improve the precision of the RBF neural network models of reservoir regulation. The boosting algorithm is used to build an integration-neural network models for reservoir regulation. Experiment results have shown good performance in the actual situation with significant economy benefits.