Artificial neural networks (ANNs) can be useful in the prediction of hydrologic variables, such as streamflow, particularly when the underlying processes have complex nonlinear interrelationships. However, conventional ANN structures suffer from network training issues that significantly limit their widespread application. This paper presents a multivariate ANN procedure entitled self-organizing linear output map (SOLO), whose structure has been designed for rapid, precise, and inexpensive estimation of network structure/parameters and system outputs. More important, SOLO provides features that facilitate insight into the underlying processes, thereby extending its usefulness beyond forecast applications as a tool for scientific investigati...
M.Ing. (Electrical and Electronic Engineering Science)Scientific workflows (SWFs) and artificial neu...
This paper traces two decades of neural network rainfall-runoff and streamflow modelling, collective...
The Artificial Neural Network (ANN) is a method of computation inspired by studies of the brain and ...
Over the last decades or so, artificial neural networks (ANNs) have become one of the most promising...
The use of an artificial neural network (ANN) is becoming common due to its ability to analyse compl...
Rainfall-runoff relationships are among the most complex hydrologic phenomena. The conceptual models...
The concept of rainfall-runoff variation is a non-linear event and highly tedious and continuously c...
Abstract: This review considers the application of artificial neural networks (ANNs) to rainfall–run...
Rainfall and surface runoff are the driving forces behind all stormwater studies and designs. The re...
Conceptual models are considered to be the best choice for describing the runoff process in a waters...
Streamflow forecasting has always been a challenging task for water resources engineers and managers...
Predicting watershed runoff is complicated because of spatial heterogeneity exhibited by various phy...
Artificial neural networks (ANNs) have been used increasingly for modelling com-plex hydrological pr...
none1noThis paper presents the application of a modular approach for real-time streamflow forecastin...
Artificial neural networks (ANNs) have been used increasingly for modelling complex hydrological pro...
M.Ing. (Electrical and Electronic Engineering Science)Scientific workflows (SWFs) and artificial neu...
This paper traces two decades of neural network rainfall-runoff and streamflow modelling, collective...
The Artificial Neural Network (ANN) is a method of computation inspired by studies of the brain and ...
Over the last decades or so, artificial neural networks (ANNs) have become one of the most promising...
The use of an artificial neural network (ANN) is becoming common due to its ability to analyse compl...
Rainfall-runoff relationships are among the most complex hydrologic phenomena. The conceptual models...
The concept of rainfall-runoff variation is a non-linear event and highly tedious and continuously c...
Abstract: This review considers the application of artificial neural networks (ANNs) to rainfall–run...
Rainfall and surface runoff are the driving forces behind all stormwater studies and designs. The re...
Conceptual models are considered to be the best choice for describing the runoff process in a waters...
Streamflow forecasting has always been a challenging task for water resources engineers and managers...
Predicting watershed runoff is complicated because of spatial heterogeneity exhibited by various phy...
Artificial neural networks (ANNs) have been used increasingly for modelling com-plex hydrological pr...
none1noThis paper presents the application of a modular approach for real-time streamflow forecastin...
Artificial neural networks (ANNs) have been used increasingly for modelling complex hydrological pro...
M.Ing. (Electrical and Electronic Engineering Science)Scientific workflows (SWFs) and artificial neu...
This paper traces two decades of neural network rainfall-runoff and streamflow modelling, collective...
The Artificial Neural Network (ANN) is a method of computation inspired by studies of the brain and ...