Alexandria Engineering Journal · 2011 · 105 citations · 22 references
Natural ResourcesHydrologyWater Resources ManagementHydrologic ModelingWater Resources EngineeringWatershed HydrologyPrecipitation ForecastingRainfall-runoff AnalysisRainfall-runoff ModelingRainfall-runoff RelationshipsShort-term Hydrologic ForecastingWatershed ModelingConceptual Model DevelopmentCross-validationCross-validation StudiesHydrological Model ValidationNeural Network ModelingPrecipitation-runoff ModelingRainfall-runoff ForecastingWater Resources Administration
Rainfall runoff models are highly useful for water resources planning and development. In the present study rainfall–runoff model based on Artificial Neural Networks (ANNs) was developed and applied on a watershed in Pakistan. The model was developed to suite the conditions in which the collected dataset is short and the quality of dataset is questionable. The results of ANN models were compared with a mathematical conceptual model. The cross validation approach was adopted for the generalization of ANN models. The precipitation used data was collected from Meteorological Department Karachi Pakistan. The results confirmed that ANN model is an important alternative to conceptual models and it can be used when the range of collected dataset is short and data is of low standard.
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Time Series Analysis: Forecasting and Control
Michael D. Geurts, George E. P. Box, Gwilym M. Jenkins · Journal of Marketing Research · 1977 · 19.3K citations
Computing, Data Science, Forecasting +11
Time Series Analysis: Forecasting and Control
Beat Kleiner · Technometrics · 1977 · 2.7K citations
Computing, Data Science, Forecasting +11