Now showing items 1-6 of 6
Fuzzy logic model for the prediction of cement compressive strength
A fuzzy logic prediction model for the 28-day compressive strength of cement mortar under standard curing conditions was created. Data collected from a cement plant were used in the model construction and testing. The input ...
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 ...
Artificial neural networks for sheet sediment transport
(Taylor & Francis, 2002-12)
Sheet sediment transport was modelled by artificial neural networks (ANNs). A three-layer feed-forward artificial neural network structure was constructed and a back-propagation algorithm was used for the training of ANNs. ...
Experimental and artificial neural network modeling study on soot formation in premixed hydrocarbon flames
The formation of soot in premixed flames of methane, ethane, propane, and butane was studied at three different equivalence ratios. Soot particle sizes, number densities, and volume fractions were determined using classical ...
Fuzzy logic algorithm for runoff-induced sediment transport from bare soil surfaces
Utilizing the rainfall intensity, and slope data, a fuzzy logic algorithm was developed to estimate sediment loads from bare soil surfaces. Considering slope and rainfall as input variables, the variables were fuzzified ...
Predicting and forecasting flow discharge at sites receiving significant lateral inflow
Two models, one linear and one non-linear, were employed for the prediction of flow discharge hydrographs at sites receiving significant lateral inflow. The linear model is based on a rating curve and permits a quick ...