Interpretation of concrete dam behaviour with artificial neural network and multiple linear regression models

2011 ◽  
Vol 33 (3) ◽  
pp. 903-910 ◽  
Author(s):  
J. Mata
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Regression Models ◽  
Linear Regression Models ◽  
Concrete Dam ◽  
Artificial Neural ◽  
Multiple Linear Regression Models

scholarly journals Development of artificial neural network and multiple linear regression models in the prediction process of the hot mix asphalt properties

2017 ◽  
Vol 44 (12) ◽  
pp. 994-1004 ◽  
Author(s):  
Ivica Androjić ◽  
Ivan Marović
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Regression Models ◽  
Prediction Models ◽  
Hot Mix Asphalt ◽  
Linear Regression Models ◽  
Artificial Neural ◽  
Multiple Linear Regression Models

The oscillation of asphalt mix composition on a daily basis significantly affects the achieved properties of the asphalt during production, thus resulting in conducting expensive laboratory tests to determine existing properties and predicting the future results. To decrease the amount of such tests, a development of artificial neural network and multiple linear regression models in the prediction process of predetermined dependent variables air void and soluble binder content is presented. The input data were obtained from a single laboratory and consists of testing 386 mixes of hot mix asphalt (HMA). It was found that it is possible and desirable to apply such models in the prediction process of the HMA properties. The final aim of the research was to compare results of the prediction models on an independent dataset and analyze them through the boundary conditions of technical regulations and the standard EN 13108-21.

Sign in / Sign up

Export Citation Format

Share Document