There are many models that have been used to simulate the rainfall-runoff relationship. The artificial neural network (ANN) model was selected to investigate an approach of improving daily runoff forecasting accuracy in terms of data preprocessing. Singular spectrum analysis (SSA) as one data preprocessing technique was adopted to deal with the model inputs and the SSA-ANN model was developed. The proposed model was compared with the original ANN model without data preprocessing and a nonlinear perturbation model (NLPM) based on ANN, i.e., the NLPM-ANN model. Eight watersheds were selected for calibrating and testing these models. Comparative study shows that the learning and training ability of ANN models can be improved by SSA and NLPM te...
A hybrid model integrating artificial neural networks and support vector regression was developed fo...
The Artificial Neural Network (ANN) is a method of computation inspired by studies of the brain and ...
The Artificial Neural Network (ANN) is a method of computation inspired by studies of the brain and ...
Accurately modeling rainfall–runoff (R–R) transform remains a challenging task despite that a wide r...
xi, 246 p. : ill. (some col.) ; 30 cm.PolyU Library Call No.: [THS] LG51 .H577P CSE 2010 WuData-driv...
A study investigating the forecast of runoff for an overland flow using the artificial neural networ...
The concept of rainfall-runoff variation is a non-linear event and highly tedious and continuously c...
Rainfall and surface runoff are the driving forces behind all stormwater studies and designs. The re...
Hydrological forecasting techniques have been dramatically developed today. However, traditional pre...
Rainfall-runoff relationships are among the most complex hydrologic phenomena. The conceptual models...
Over the last decades or so, artificial neural networks (ANNs) have become one of the most promising...
Time-series analysis techniques for improving the real-time flood forecasts issued by a deterministi...
Abstract: Rainfall is very important parameter in hydrological model. Many techniques and models hav...
Abstract: The present study aims to utilize an Artificial Neural Network (ANN) to modeling the rainf...
Accurate streamflow forecasting can help minimizing the negative impacts of hydrological events such...
A hybrid model integrating artificial neural networks and support vector regression was developed fo...
The Artificial Neural Network (ANN) is a method of computation inspired by studies of the brain and ...
The Artificial Neural Network (ANN) is a method of computation inspired by studies of the brain and ...
Accurately modeling rainfall–runoff (R–R) transform remains a challenging task despite that a wide r...
xi, 246 p. : ill. (some col.) ; 30 cm.PolyU Library Call No.: [THS] LG51 .H577P CSE 2010 WuData-driv...
A study investigating the forecast of runoff for an overland flow using the artificial neural networ...
The concept of rainfall-runoff variation is a non-linear event and highly tedious and continuously c...
Rainfall and surface runoff are the driving forces behind all stormwater studies and designs. The re...
Hydrological forecasting techniques have been dramatically developed today. However, traditional pre...
Rainfall-runoff relationships are among the most complex hydrologic phenomena. The conceptual models...
Over the last decades or so, artificial neural networks (ANNs) have become one of the most promising...
Time-series analysis techniques for improving the real-time flood forecasts issued by a deterministi...
Abstract: Rainfall is very important parameter in hydrological model. Many techniques and models hav...
Abstract: The present study aims to utilize an Artificial Neural Network (ANN) to modeling the rainf...
Accurate streamflow forecasting can help minimizing the negative impacts of hydrological events such...
A hybrid model integrating artificial neural networks and support vector regression was developed fo...
The Artificial Neural Network (ANN) is a method of computation inspired by studies of the brain and ...
The Artificial Neural Network (ANN) is a method of computation inspired by studies of the brain and ...