Answers are grounded in this paper and cite their sources.
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.
No takes yet. Share an insight, caveat, or question.
Laio et al. (2003) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: