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Short-term Streamflow Forecasting: ARIMA Vs Neural Networks

机译:短期流流预测:Arima VS神经网络

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Streamflow forecasting is very important for water resources management and flood defence. In this paper two forecasting methods are compared: ARIMA versus a multilayer perceptron neural network. This comparison is done by forecasting a streamflow of a Mexican river. Surprising results showed that in a monthly basis, ARIMA has lower prediction errors than this Neural Network.
机译:流流预测对于水资源管理和防洪非常重要。本文比较了两种预测方法:Arima与多层的感知者神经网络。这种比较是通过预测墨西哥河流的流出来完成的。令人惊讶的结果表明,按月,阿米马的预测误差较低,而不是这种神经网络。

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