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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Landslide易感性主要影响因素

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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损害。滑坡易感性和危险区分区是减少山体滑坡风险的有效方法。有许多因素对滑坡易感性做出贡献。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。本文提出了一种与进化算法和神经网络混合的策略。在用神经网络培训历史数据之后,客观函数可以通过可行的神经网络模式替换。然后,可以在多目标进化算法中嵌入给定的神经网络模型来遵循进化计算。给定的方法适用于中国西南部宫县。其结果具有实践并证明有效。

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