Abstract
In this chapter1, based on the normal diffusion and the feedforward neural network with backpropagation algorithm (BP), we suggest a hybrid fuzzy neural network to estimate isoseismal area by earthquake magnitude. In section 9.1 we give the outline of estimation of isoseismal area. In section 9.2, we give a brief review of current methods for the construction of fuzzy relationships. Section 9.3 suggests the information diffusion function to produce if-then rules from observations. In section 9.4, we propose a model for pattern smoothing to assist a BP neural network to acquire knowledge from the data. In section 9.5, we give the architecture of the hybrid model which consists of an information-diffusion approximate reasoning and a conventional BP neural network. In section 9.6, we use the model to estimate isoseismal area by earthquake magnitude. The chapter is then summarized with a conclusion in section 9.7.
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Huang, C., Shi, Y. (2002). Estimation of Isoseismal Area. In: Towards Efficient Fuzzy Information Processing. Studies in Fuzziness and Soft Computing, vol 99. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1785-0_9
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DOI: https://doi.org/10.1007/978-3-7908-1785-0_9
Publisher Name: Physica, Heidelberg
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