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Generalized versus non-generalized neural network model for multi-lead inflow forecasting at Aswan High Dam
non-generalized neural network model multi-lead inflow
2011/3/15
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....
An experiment on the evolution of an ensemble of neural networks for streamflow forecasting
experiment evolution ensemble neural networks streamflow forecasting
2010/4/7
We present an experiment on fifty multilayer perceptrons trained for streamflow forecasting on three watersheds using bootstrapped input series. This type of neural network is common in hydrology and ...
Forecasting high waters at Venice Lagoon using chaotic time series analysis and nonlinear neural networks
high waters Venice Lagoon chaotic time series analysis nonlinear neural networks
2009/12/7
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...
Data-based mechanistic modelling and forecasting of hydrological systems
Data-based mechanistic modelling forecasting hydrological systems
2009/12/7
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...
Long-range climate forecasting and its use for water management in the Pacific Northwest region of North America
Long-range climate forecasting water management Pacific Northwest region North America
2009/12/7
Ongoing research by the Climate Impacts Group at the University of Washington focuses on the use of recent advances in climate research to improve streamflow forecasts at seasonal-to-interannual, deca...
Improved non-linear transfer function and neural network methods of flow routing for real-time forecasting
non-linear transfer function neural network methods flow routing real-time forecasting
2009/12/4
Data-based methods of flow forecasting are becoming increasingly popular due to their rapid development times, minimum information requirements, and ease of real-time implementation, with transfer fun...
Rainfall and runoff forecasting with SSA–SVM approach
Rainfall and runoff forecasting SSA–SVM approach
2009/12/4
Real time operation studies such as reservoir operation, flood forecasting, etc., necessitates good forecasts of the associated hydrologic variable(s). A significant improvement in such forecasting ca...
Neural network rainfall-runoff forecasting based on continuous resampling
Neural network rainfall-runoff forecasting continuous resampling
2009/12/4
Most neural network hydrological modelling has used split-sample validation to ensure good out-of-sample generalisation and thus safeguard each potential solution against the danger of overfitting. Ho...
EC-SVM approach for real-time hydrologic forecasting
EC-SVM approach real-time hydrologic forecasting
2009/12/4
This study demonstrates a combined application of chaos theory and support vector machine (SVM) in the analysis of chaotic time series with a very large sample data record. A large data record is ofte...
Efficient implementation of inverse approach for forecasting hydrological time series using micro GA
Efficient implementation inverse approach hydrological time series micro GA
2009/12/4
This paper implements the inverse approach for forecasting hydrological time series in an efficient way using a micro-GA (mGA) search engine. The inverse approach is based on chaos theory and it invol...
Flash-flood forecasting by means of neural networks and nearest neighbour approach–a comparative study
Flash-flood forecasting neural networks nearest neighbour approach
2009/11/9
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...
Combination of a Conceptual Model and an Autoregressive Error Model for Improving Short Time Forecasting
Combination Conceptual Model Autoregressive Error Model
2009/10/28
An autoregressive error model has been tested on the residuals of the conceptual
HBV-model for the EmAn catchment. The autoregresslve model gives
considerable improvements for real shorttime forecas...
Development and Application of a Storage Model for River Flow Forecasting
Development Application Storage Model River Flow Forecasting
2009/10/28
A lumped sequential river flow forecasting model is outlined. It is shown to be
flexible in both temporal and spatial scales, thereby allowing simulations to be
undertaken for a wide range of practi...
A Mathematical Modelling System for Flood Forecasting
Mathematical Modelling System Flood Forecasting
2009/10/28
In this paper comprehensive simulation models are presented which can forecast
the streamflow in real time at various points in river systems and provide a
tool for identifying improvements of the r...
On Soil Retention Curves and Hydrological Forecasting in Ungauged Catchments
Soil Retention Curves Hydrological Forecasting Ungauged Catchments
2009/10/28
In many physically based hydrological models, there is the requirement to
specify the suction-moisture curve of the soil system. This paper shows that
where the suction moisture curve is known, then...