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Estimating the relationship between isoseismal area and earthquake magnitude by a hybrid fuzzy-neural-network method

机译:用模糊神经网络混合法估算等震面积与地震烈度的关系

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摘要

Utilizing information diffusion method and artificial neural networks, we propose in this paper a hybrid fuzzy neural network to estimate the relationship between isoseismal area and earthquake magnitude. we focus on the study of incompleteness and contradictory nature of patterns in scantly historical earthquake records. Information diffusion method is employed to construct fuzzy relationships which are equal to the number of observations. Integration of the relationships can change the contradictory patterns into more compatible ones which, in turn, can smoothly and quickly train the feed forward neural network with backpropagation algorithm (BP) to obtain the final relationship. A practical application is employed to show the superiority of the model.
机译:本文利用信息扩散方法和人工神经网络,提出了一种混合模糊神经网络来估计等震面积与地震烈度之间的关系。我们专注于研究很少的历史地震记录中模式的不完整性和矛盾性。信息扩散法被用于构造与观察次数相等的模糊关系。关系的集成可以将矛盾的模式改变为更兼容的模式,从而可以平滑快速地使用反向传播算法(BP)训练前馈神经网络以获得最终关系。实际应用表明了该模型的优越性。

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