Претраживање
Приказ резултата 1-6 од 6
Construction cost estimation of reinforced and prestressed concrete bridges using machine learning
(Građevinar, 2021)
Seven state-of-the-art machine learning techniques for estimation of construction
costs of reinforced-concrete and prestressed concrete bridges are investigated in this
paper, including artificial neural networks (ANN) ...
Spatio-temporal interpolation of climate elements using geostatistics and machine learning
(Универзитет у Београду, Грађевински факултет, 09-04-2021)
High resolution daily maps for climate elements are a valuable source of information and serve as aninput for climatology, meteorology, agriculture, hydrology, ecology, and many other research areasand disciplines. ...
Prediction of aircraft noise using machine learning
(2021)
In this paper an attempt has been made to predict and evaluate the aircraft-induced noise using model
developed by means of machine learning. First step in the development of the model was to artificially
calculate noise ...
Primena mašinskog učenja za procenu cena i količina radova pri izgradnji stambenih i stambeno-poslovnih objekata
(Udruženje inženjera građevinarstva, geotehnike, arhitekture i urbanista "Izgradnja", 2021)
Ovaj rad se bavi problemom procena potrebnih količina radova, kao i koštanja izgradnje stambenih i stambeno-poslovnih objekata korišćenjem algoritama mašinskog učenja. Osnovni cilj je analiza mogućnosti primene mašinskog ...
Prediction of aircraft noise using machine learning
(Silesian University Press, Gliwice, Poland, 2021)
In this paper an attempt has been made to predict and evaluate the aircraft-induced noise using model developed by means of machine learning. First step in the development of the model was to artificially calculate noise ...
Rapid earthquake loss assessment based on machine learning and representative sampling
(Earthquake Spectra, 2021)
This paper proposes a new framework for rapid earthquake loss assessment based on a machine learning damage classification model and a representative sampling algorithm. A Random Forest classification model predicts a ...