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In a flood-prone region, quick and accurate flood forecasting is imperative. It can extend the lead time for issuing disaster warnings and allow sufficient time for habitants in hazardous areas to take appropriate action, such as evacuation. In this paper, two hybrid models based on recent artificial intelligence technology, namely, genetic algorithm-based artificial neural network (ANN-GA) and adaptive-network-based fuzzy inference system (ANFIS), are employed for flood forecasting in adoi:10.1061/(asce)1084-0699(2005)10:6(485) fatcat:xrxfmt6aafaynlu2o3dli7otjq