Now showing items 1-6 of 6
Principle component analysis in conjuction with data driven methods for sediment load prediction
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) ...
Modern optimization methods in water resources planning, engineering and management
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 ...
Reverse flood routing in natural channels using genetic algorithm
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 ...
The use of GA-ANNs in the modelling of compressive strength of cement mortar
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 ...
Predicting mean and bankfull discharge from channel cross-sectional area by expert and regression methods
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 ...
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 ...