80 research outputs found
Artificial neural network models for estimating regional reference evapotranspiration based on climate factors
Evaluation of soft computing and regression-based techniques for the estimation of evaporation
A comparison of nonlinear flood forecasting methods
Two nonlinear models, nonlinear prediction (NLP) and artificial neural networks (ANN), are compared for multivariate flood forecasting. For NLP the calibration of the locally linear model is quite simple, while for ANN the validation and identification of the model can be cumbersome, mainly because of overfitting. Very good results are obtained with the two methods: NLP performs slightly better at short forecast times while the situation is reversed for longer times
Application of a neural network model in establishing a stage-discharge relationship for a tidal river
Numerically modelling groundwater in an arid area with ANN-generated dynamic boundary conditions
Assessment of a conceptual hydrological model and artificial neural networks for daily outflows forecasting
Modelling groundwater levels in an urban coastal aquifer using artificial neural networks
Impacts of climate change and human activities on surface runoff in the Dongjiang River basin of China
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