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Hourly flood forecasting of Chumporn River with a neural network model

机译:基于神经网络模型的钦蓬河每小时洪水预报。

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摘要

An artificial neural network model was developed to analyse and forecast the behaviour of the Chumporn River in Thailand during year 1990. The model makes use of the upstream river gauging stations (X.46 & X.64) and predicts the water level of the river at station X.158 at Khlong Tha Taphao, Chumporn. Model predictions up to six hour ahead are very accurate (i.e. coefficient of efficiency is more than 95%) when the model is used with a hourly time horizon. Increasing the time horizon decreases the accuracy of the model and also amplifies the phase errors. The time horizon of the input data and the response time of the river basin limit performance of the model.
机译:开发了一个人工神经网络模型来分析和预测泰国1990年的Chumporn河的行为。该模型利用上游测河站(X.46和X.64)并预测该河的水位在Chumporn的Khlong Tha Taphao的X.158站。当模型在每小时的时间范围内使用时,模型预测最多可以提前六个小时(即效率系数大于95%)进行预测。时间范围的增加会降低模型的准确性,还会放大相位误差。输入数据的时间范围和流域的响应时间限制了模型的性能。

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