Now showing items 1-5 of 5
Genetic algorithm-artificial neural network model for the prediction of germanium recovery from zinc plant residues
(Maney Publishing, 2002-09)
A multi-layer, feed-forward, back-propagation learning algorithm was used as an artificial neural network (ANN) tool to predict the extraction of germanium from zinc plant residues by sulphuric acid leaching. A genetic ...
Artificial neural network (ANN) prediction of compressive strength of VARTM processed polymer composites
A three layer feed forward artificial neural network (ANN) model having three input neurons, one output neuron and two hidden neurons was developed to predict the ply-lay up compressive strength of VARTM processed E-glass/ ...
Predicting longitudinal dispersion coefficient in natural streams by artificial neural network
(American Society of Civil Engineers, 2005-11)
An-artificial neural network (ANN) model was developed to predict the longitudinal dispersion coefficient in natural streams and rivers. The hydraulic variables [flow discharge (Q), flow depth (H), flow velocity (U), shear ...
ANN and fuzzy logic models for simulating event-based rainfall-runoff
(American Society of Civil Engineers, 2006-12)
This study presents the development of artificial neural network (ANN) and fuzzy logic (FL) models for predicting event-based rainfall runoff and tests these models against the kinematic wave approximation (KWA). A three-layer ...
Closure to "ANN and fuzzy logic models for simulating event-based rainfall-runoff" by Gokmen Tayfur and Vijay P. Singh
(American Society of Civil Engineers, 2008-09)
We would like to thank Dr. Wong for his interest in and thoughts on our analysis of runoff hydrograph prediction and the goodnessof-fit measurement. We agree that visual comparison of simulated and measured hydrographs is ...