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洪水灾害承灾体易损性模型一般是非线性的、动态的。人工神经网络具有逼近任意非线性映射的特性。本文给出了用于洪水灾害承灾体易损性建模的基于遗传算法的神经网络模型,阐述了其基本原理和算法,并结合实例说明了其应用。
Flood damage disaster vulnerability models are generally nonlinear and dynamic. Artificial neural networks have the property of approximating arbitrary nonlinear mappings. In this paper, a neural network model based on genetic algorithm for modelling the vulnerability of flood disaster bearing disasters is presented. The basic principle and algorithm of the neural network are described. The application of the model is illustrated with an example.