Napredna pretraga

Pregled bibliografske jedinice broj: 887865

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


Androjić, Ivica; Marović, Ivan
Development of artificial neural network and multiple linear regression models in the prediction process of the hot mix asphalt properties // Canadian journal of civil engineering, 44 (2017), 12; 994-1004 doi:10.1139/cjce-2017-0300 (međunarodna recenzija, članak, znanstveni)


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

Autori
Androjić, Ivica ; Marović, Ivan

Izvornik
Canadian journal of civil engineering (0315-1468) 44 (2017), 12; 994-1004

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Hot mix asphalt ; artificial neural networks ; multiple linear regression ; prediction process

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Građevinarstvo, Temeljne tehničke znanosti, Projektni menadžment



POVEZANOST RADA


Ustanove
Građevinski fakultet, Rijeka

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Uključenost u ostale bibliografske baze podataka:


  • Compendex (EI Village)
  • INSPEC


Citati