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Kayastha, N. (author), Solomatine, D.P. (author)Single hydrological model or model calibrated on single objective function often cannot capture all components of a water motion process. One possibility is building several specialized models each of which responsible for a particular sub-process (e.g., high flows or low flows), and combining them using dynamic weights – thus forming a...conference paper 2014
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Kayastha, N. (author), Solomatine, D.P. (author), Lal Shrestha, D. (author)In the MLUE method (reported in Shrestha et al. [1, 2]) we run a hydrological model M for multiple realizations of parameters vectors (Monte Carlo simulations), and use this data to build a machine learning model V to predict uncertainty (quantiles) of the model M output. In this paper, for model V, we employ three machine learning techniques,...conference paper 2014