Now showing items 1-5 of 5
Artificial neural networks to predict daylight illuminance in office buildings
A prediction model was developed to determine daylight illuminance for the office buildings by using artificial neural networks (ANNs). Illuminance data were collected for 3 months by applying a field measuring method. ...
Quantification of CaCO3-CaSO3·0.5H 2O-CaSO4·2H2O mixtures by FTIR analysis and its ANN model
A new quantitative analysis method for mixtures of calcium carbonate (CaCO3), calcium sulphite hemihydrate (CaSO 3·1/2H2O) and gypsum (CaSO 4·2H2O) by FTIR spectroscopy is developed. The method involves the FTIR analysis ...
Evaluating the knowledge management practices of construction firms by using importance-comparative performance analysis maps
(American Society of Civil Engineers, 2011-12)
The emergence of the effective management of knowledge resources as a key factor in gaining and sustaining competitive advantage presents new challenges to construction firms. Evaluating knowledge management practices is ...
Soft computing and regression modelling approaches for link-capacity functions
(Czech Technical University in Prague, 2016)
Link-capacity functions are the relationships between the fundamental traffic variables like travel time and the flow rate. These relationships are important inputs to the capacity-restrained traffic assignment models. ...
Comparative study of a building energy performance software (KEP-IYTE-ESS) and ANN-based building heat load estimation
The several parameters affect the heat load of a building; geometry, construction, layout, climate and the users. These parameters are complex and interrelated. Comprehensive models are needed to understand relationships ...