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Select landslide susceptibility main affecting factors by multi-objective optimization algorithm

机译:通过多目标优化算法选择滑坡敏感性主要影响因素

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Landslide often causes great damage to human society. Landslide susceptibility and hazard zoning is an efficient way to reduce landslides risk. There are many factors make contribution to landslide susceptibility. Artificial neural network has been devoted to this area but still need to improve its effectiveness. This paper present a strategy mixed with evolutionary algorithm and neural network. After training on historical data with neural network, the objective function could be replaced by feasible neural network mode. Then, evolutionary computation could be followed by embedding the given neural network model in multi-objective evolutionary algorithm. The given method was applied to Miyi county, southwest China. Its result have take into practice and proved effective.
机译:滑坡经常对人类社会造成巨大破坏。滑坡敏感性和危险性分区是降低滑坡风险的有效方法。造成滑坡敏感性的因素很多。人工神经网络已经致力于这一领域,但仍需要提高其有效性。本文提出了一种融合了进化算法和神经网络的策略。用神经网络训练历史数据后,目标函数可以用可行的神经网络模式代替。然后,通过将给定的神经网络模型嵌入多目标进化算法中,可以进行进化计算。给定的方法应用于中国西南的密邑县。其结果已付诸实践并证明是有效的。

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