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Fuzzy time series for real-time flood forecasting

机译:实时洪水预报的模糊时间序列

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This study applied fuzzy time series (FTS) analysis to develop a real-time flood forecasting model to forecast typhoon flood discharges. Two crucial factors that influence the performance of FTS are the partition of intervals of the variable and the defuzzification method. This study examined the effects of various interval lengths and two defuzzification methods, the centroid and the midpoint methods, on the model performance. Criteria of model completeness and consistency principle were used to determine the effective interval length, and analytic results showed that the midpoint method outperforms the centroid method. Two structures of forecasting models were proposed to make multiple-hour-ahead flood forecasts. Validation results from typhoon flood events in the Wu River in Taiwan showed that the proposed FTS model, which is novel in hydrologic forecasting, can effectively forecast flood discharges.
机译:本研究应用模糊时间序列(FTS)分析建立了实时洪水预报模型,以预报台风洪水流量。影响FTS性能的两个关键因素是变量间隔的划分和去模糊方法。这项研究检查了各种间隔长度和两种去模糊方法(质心和中点方法)对模型性能的影响。使用模型完整性和一致性原理的准则来确定有效间隔长度,分析结果表明,中点方法优于质心方法。提出了两种预测模型结构来进行数小时提前洪水预报。台湾吴江台风洪水事件的验证结果表明,本文提出的FTS模型在水文预报中是新颖的,可以有效地预报洪水流量。

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