Pregled bibliografske jedinice broj: 767924
Analysis of neural network responses in calibration of microsimulation traffic model
Analysis of neural network responses in calibration of microsimulation traffic model // Electronic journal of the Faculty of Civil Engineering Osijek - e-GFOS, 10 (2015), 67-76 doi:10.13167/2015.10.8 (domaća recenzija, članak, znanstveni)
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Naslov
Analysis of neural network responses in
calibration of microsimulation traffic model
Autori
Ištoka Otković, Irena ; Varevac, Damir ; Šraml, Matjaž
Izvornik
Electronic journal of the Faculty of Civil Engineering Osijek - e-GFOS (1847-8948) 10
(2015);
67-76
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
microsimulation traffic models ; calibration ; response of neural networks ; traveling time ; queue parameters
Sažetak
Microsimulation models are frequently used in traffic analysis. Various optimization methods are used in calibration, and the one method that has shown success is neural networks. This paper shows the responses of neural networks during calibration of a microsimulation traffic model. We analyzed two calibration methods by applying neural networks and comparing their neural network learning (according to their achieved correlation and the mean error of prediction) and their generalization ability (comparison of generalization results was analyzed in two steps). The best correlation between the microsimulation results and neural network prediction was 88.3%, achieved for the traveling time prediction, on which the first calibration method is based.
Izvorni jezik
Engleski
Znanstvena područja
Građevinarstvo, Računarstvo, Tehnologija prometa i transport
POVEZANOST RADA
Ustanove:
Građevinski i arhitektonski fakultet Osijek
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Emerging Sources Citation Index (ESCI)
Uključenost u ostale bibliografske baze podataka::
- CAB Abstracts
- INSPEC