Donald H. Burn

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[1] Recent theoretical and empirical studies show that the generalization ability of artificial neural networks can be improved by combining several artificial neural networks in redundant ensembles. In this paper, a review is given of popular ensemble methods. Six approaches for creating artificial neural network ensembles are applied in pooled flood(More)
Metamodelling is an increasingly more popular approach for alleviating the computational burden associated with computationally intensive optimization/management problems in environmental and water resources systems. Some studies refer to the metamodelling approach as function approximation, surrogate modelling, response surface methodology or model(More)
Understanding the hydro-climatological controls on floods is fundamental for estimating flood frequency. The river flood regime is a reflection of a complex catchment hydrological response to flood producing processes. Hence, the catchment similarity in a flood regime is a feasible basis for identifying flood frequency pooling groups used in regional(More)
A new technique is developed for identifying groups for regional flood frequency analysis. The technique uses a clustering algorithm as a starting point for partitioning the collection of catchments. The groups formed using the clustering algorithm are subsequently revised to improve the regional characteristics based on three requirements that are defined(More)
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