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Conference Papers Year : 2013

Flash flood forecasting using Support Vector Regression: An event clustering based approach

Abstract

We present a new machine learning approach to flash flood forecasting in the absence of rainfall forecasts, based on the agglomerative hierarchical clustering of flood events. Each cluster contains events whose models have similar behaviors. Specific Support Vector Regression models are then trained from each cluster. The test results show that a specific model may be more accurate than a general model trained from all floods present in the training database.
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Dates and versions

hal-04169332 , version 1 (24-07-2023)

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Khaled Boukharouba, Pierre Roussel, Gerard Dreyfus, Anne Johannet. Flash flood forecasting using Support Vector Regression: An event clustering based approach. 2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP), Sep 2013, Southampton, United Kingdom. pp.1-6, ⟨10.1109/MLSP.2013.6661958⟩. ⟨hal-04169332⟩
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