洪水位之即時機率預報－結合支撐向量機與模糊推理

Real-time Probabilistic Flood Stage Forecasting Using Support Vector Machines and Fuzzy Inference

陳憲宗(Shien-Tsung Chen) ； 游保杉(Pao-Shan Yu)

《農業工程學報》 53卷4期 (2007/12) Pp. 1-20

https://doi.org/10.29974/JTAE.200712.0001

摘要

本研究提出一套結合定值預報與誤差機率估算的方法、來實際進行洪水水位的即時機率預報。方法首先採用支撐向量機模式來建立定值水位預報模式，提供未來一至六小時的即時水水位預報值，接著利用改良式模糊推理模式來推求預報誤差的機率分布函數，再結合定值水位預報值及預報誤差的機率分布函數，則可得到預報水位的機率不分布函數。本機率預報方法以蘭陽大橋爲案例，實際應用於未來一至六小時的即時洪水位機率預報，經針對十二場驗證洪水事件的95%信賴區間預報，以及針對預報水位超過警戒水位發生機率的探討，顯示本研究提出之機率預報方法具有良好的預報效能及實用性。

關鍵字

洪水預報 ； 機率預報 ； 支撐向量機 ； 模糊推理模式

並列摘要

This study is to perform real-time probabilistic flood stage forecasting. The proposed method consists of a deterministic stage forecast derived from the support vector machines, and a probability distribution of forecast error based on the fuzzy inference model. The probabilistic flood stage forecasts can then be obtained by combining the deterministic stage forecasts with the error probability distributions. The proposed approach is applied to the Lang-Yang River in Taiwan pertaining to validation events of six flash floods. The probability distributions of stage forecasts one to six hours ahead are made, and the predictive uncertainty information is presented and discussed in various aspects. Forecasting results examined by forecast hydrographs with a 95% confidence interval, and the percentages of data included in the confidence region, indicate the effectiveness of proposed methodology.

並列關鍵字

Flood forecasting ； Probabilistic forecasting ； Support vector regression ； Fuzzy inference