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van der Heijden, T.J.T. (author), Palensky, P. (author), Abraham, E. (author)In this paper we propose a Quantile Regression Deep Neural Network capable of forecasting multiple quantiles in one model using a combined quantile loss function, and apply it to probabilistically forecast the prices of 8 European Day Ahead Markets. We show that the proposed loss function significantly reduces the quantile crossing problem to ...conference paper 2021
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Verkade, J.S. (author), Brown, J. D. (author), Davids, F. (author), Reggiani, P. (author), Weerts, A. H. (author)Two statistical post-processing approaches for estimation of predictive hydrological uncertainty are compared: (i) ‘dressing’ of a deterministic forecast by adding a single, combined estimate of both hydrological and meteorological uncertainty and (ii) ‘dressing’ of an ensemble streamflow forecast by adding an estimate of hydrological...journal article 2017