This study presents an artificial neural network (ANN) model to predict the values of the longitudinal dispersion coefficient ) ( l D in rivers from their main hydraulic parameters. The model can be considered as a useful aid to water quality monitoring in rivers. The ANN model is a relatively new promising technique which can make use of the river width, depth, velocity, and shear velocity for...

Zhengfu Rao (corresponding author) School of Civil Engineering and Geosciences, University of Newcastle, Newcastle upon Tyne NE1 7RU, UK Tel.: +44 1793 816359 Fax: +44 1793 812 089 E-mail: [email protected] Fernando Alvarruiz Departamento de Sistemas Informáticos y Computación, Universidad Politecnica de Valencia, Valencia 46022, Spain As part of the POWADIMA research project, this paper describ...

In order to measure precipitation as the main variable for estimating the runoff and designing hydraulic structures, the satellite algorithm products that have the proper spatial and temporal coverage, can be used. In this study, at first, the daily streamflow simulation of Sarough-Cahy River from the Zarinehroud basin was conducted through the artificial neural network (ANN) and ground data of...

A new computer program, 1DTempPro, is presented for the analysis of vertical one-dimensional (1D) temperature profiles under saturated flow conditions. 1DTempPro is a graphical user interface to the U.S. Geological Survey code Variably Saturated 2-Dimensional Heat Transport (VS2DH), which numerically solves the flow and heat-transport equations. Pre- and postprocessor features allow the user to...

To effectively predict the thermal conductivity and viscosity of alumina (Al₂O₃)-water nanofluids, an artificial neural network (ANN) approach was investigated in the present study. Firstly, using a two-step method, four Al₂O₃-water nanofluids were prepared respectively by dispersing different volume fractions (1.31%, 2.72%, 4.25%, and 5.92%) of nanoparticles with the average diameter of 30 nm....

hydraulic attributes play important role in hydrological studies, soil conservation, designing irrigation and drainage systems, soil conservation, and controlling soil erosion in watersheds. their measurements are very tedious and time consuming and due to high spatial variability, a large number of measurements are required for obtaining reliable values. nowadays, prediction of these attribute...

the examination of available vapor pressure data in the case of the methane, ethane, propane and butane halogenated refrigerants, allowed recommendations of standard equations for this property. in this study, three new models include a general correlation; a substance-dependent correlation and an artificial neural network (ann) approach have been developed to estimate the saturated vapor press...

We present a methodology to account for the stochastic nature of hydraulic conductivity during the design of pump-and-treat systems for aquifer cleanup. The methodology (I) uses a genetic algorithm to find the global optimal solution and (2) incorporates a neural network to model the response surface within the genetic algorithm. We apply the methodology for a real example and different optimiz...

background : in medical studies, when the joint prediction about occurrence of two events should be anticipated, a statistical bivariate model is used. due to the limitations of usual statistical models, other methods such as artificial neural network (ann) and hybrid models could be used. in this paper, we propose a hybrid artificial neural network-genetic algorithm (ann-ga) model to predictio...