Search
Now showing items 1-7 of 7
The use of GA-ANNs in the modelling of compressive strength of cement mortar
(Elsevier, 2003-07)
In this paper, results of a project aimed at modelling the compressive strength of cement mortar under standard curing conditions are reported. Plant data were collected for 6 months for the chemical and physical properties ...
GA-optimized model predicts dispersion coefficient in natural channels
(IWA Publishing, 2009)
Models whose parameters were optimized by genetic algorithm (GA) were developed to predict the longitudinal dispersion coefficient in natural channels. Following the existing equations in the literature, ten different ...
Predicting mean and bankfull discharge from channel cross-sectional area by expert and regression methods
(Springer, 2011-03)
This study employed four methods-non-linear regression, fuzzy logic (FL), artificial neural networks (ANNs), and genetic algorithm (GA)-based nonlinear equation-for predicting mean discharge and bank-full discharge from ...
Ampirik yöntemlerle Gediz Nehri için askıda katı madde yükü tahmini
(TMMOB İnşaat Mühendisleri Odası, 2011-04)
It is essential to predict suspended sediment load for understanding river morphology, design of dams, water supply problems, management of reservoirs and determination of pollution levels in rivers. The suspended sediment ...
Reverse flood routing in natural channels using genetic algorithm
(Springer, 2015-09-13)
Establishing a clear overview of data discharge availability for water balance modelling in basins is a priority in Europe, and in the particular in the framework of the system of Economic and Environmental Accounts for ...
Modern optimization methods in water resources planning, engineering and management
(Springer, 2017-08)
Mathematical (analytical, numerical and optimization) models are employed in many disciplines including the water resources planning, engineering and management. These models can vary from a simple black-box model to a ...
Principle component analysis in conjuction with data driven methods for sediment load prediction
(Springer, 2013-05)
This study investigates sediment load prediction and generalization from laboratory scale to field scale using principle component analysis (PCA) in conjunction with data driven methods of artificial neural networks (ANNs) ...