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Artificial neural networks (ANN) have been found efficient, particularly in problems where characteristics of the processes are stochastic and difficult to describe using explicit mathematical models....
Time series analysis using nonlinear dynamics systems theory and multilayer neural networks models have been applied to the time sequence of water level data recorded every hour at 'Punta della Salute...
The paper presents a data-driven approach to the modelling and forecasting of hydrological systems based on nonlinear time-series analysis. Time varying parameters are estimated using a combined Kalma...
In this paper, Multi-Layer Perceptron and Radial-Basis Function Neural Networks, along with the Nearest Neighbour approach and linear regression are utilized for flash-flood forecasting in the mountai...
This paper compares event-based and continuous hydrological modelling approaches for real-time forecasting of river flows. Both approaches are compared using a lumped hydrologic model (whose structure...
This paper compares the performance of two artificial neural network (ANN) models – the multi layer perceptron (MLP) and the radial basis function network (RBF) – with a stepwise multiple linear regre...
Snow, whilst not a dominant feature of Britain's maritime climate, can exert a significant influence on major floods through its contribution as snowmelt. Flood warning systems which fail to take acco...
Catastrophic disasters afflicting human society are often triggered by tsunamis, earthquakes, widespread flooding, and weather and climate events. As human populations increasingly move into geographi...

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