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Flash floods forecasting without rainfalls forecasts by recurrent neural networks. Case study on the Mialet basin (Southern France)

机译:通过经常性神经网络,闪现洪水预测没有降雨预测。 Mialet盆地(法国南部)案例研究

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The feasibility of flash flood prediction without rainfall forecasts nor previous discharge is considered. After a presentation of the important stakes involved in this task (23 fatalities in the Var event in June 2010, France) the important stage of variable and complexity selection is addressed for the small basin of Mialet (a part of the Gardon d'Anduze basin, in Southern France). Considering two architectures inspired from the multilayer perceptron, both designs and performances are presented and the model considering the linear and non-linear behaviors independently is proved to be the better. Generalization properties are assessed for four predictions up to two hours ahead thereby allowing an early warning of the population.
机译:闪蒸洪水预测无降雨预测的可行性也是考虑到以前的放电。在这项任务中涉及的重要赌注(2010年6月的var活动中的23个死亡率)之后,为Mialet的小盆地(Gardon d'Anduze盆地的一部分)解决了变量和复杂性选择的重要阶段,在法国南部)。考虑到来自多层erceptron的两个建筑,呈现了设计和性能,并且考虑了线性和非线性行为的模型被证明是更好的。普遍性地评估了四个预测,从而提高了两个小时,从而允许人口的预警。

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