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Models of A-K Neural Network for Evaluation of Water Resources Abundance

Back propagation and radial basis function neural network methods have been applied to hydrology and water resources areas due to theirs powerful learning ability and many good results have been achieved, but there are no known samples for learning, these methods can not be applied successfully. In this paper, the model of A K neural network, which has plasticity, and is unsupervised, is worked out. The application of A K network models in the evaluation of water resources in west of China shows that it can deal with many problems about classification ideally, and is worthwhile to be popularized.