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A fuzzy neural network model based on fuzzy clustering and its applications

机译:基于模糊聚类及其应用的模糊神经网络模型

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Fuzzy neural network, which is based on fuzzy theory and BP neural network, plays an important role in practical. But the difficulty is how to construct its structure model. In this paper, according to the hypostasis of hidden layer, a fuzzy neural network model based on fuzzy clustering is brought forward, in which features of the samples are extracted and output information is synthetically considered. And a satisfied result is reached in the application of oil-gas recognition in Tarim Oilfield.
机译:基于模糊理论和BP神经网络的模糊神经网络在实用中起着重要作用。但难度是如何构建其结构模型。本文根据隐藏层的超比,提出了一种基于模糊聚类的模糊神经网络模型,其中提取了样本的特征,并合成了输出信息。在塔里木油田的油气识别中达成了满足的结果。

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