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Pregled bibliografske jedinice broj: 767924

Analysis of neural network responses in calibration of microsimulation traffic model


Ištoka Otković, Irena; Varevac, Damir; Šraml, Matjaž
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)


CROSBI ID: 767924 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

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

Profili:

Avatar Url Damir Varevac (autor)

Avatar Url Irena Ištoka Otković (autor)

Poveznice na cjeloviti tekst rada:

doi e-gfos.gfos.hr e-gfos.gfos.hr

Citiraj ovu publikaciju:

Ištoka Otković, Irena; Varevac, Damir; Šraml, Matjaž
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)
Ištoka Otković, I., Varevac, D. & Šraml, M. (2015) Analysis of neural network responses in calibration of microsimulation traffic model. Electronic journal of the Faculty of Civil Engineering Osijek - e-GFOS, 10, 67-76 doi:10.13167/2015.10.8.
@article{article, author = {I\v{s}toka Otkovi\'{c}, Irena and Varevac, Damir and \v{S}raml, Matja\v{z}}, year = {2015}, pages = {67-76}, DOI = {10.13167/2015.10.8}, keywords = {microsimulation traffic models, calibration, response of neural networks, traveling time, queue parameters}, journal = {Electronic journal of the Faculty of Civil Engineering Osijek - e-GFOS}, doi = {10.13167/2015.10.8}, volume = {10}, issn = {1847-8948}, title = {Analysis of neural network responses in calibration of microsimulation traffic model}, keyword = {microsimulation traffic models, calibration, response of neural networks, traveling time, queue parameters} }
@article{article, author = {I\v{s}toka Otkovi\'{c}, Irena and Varevac, Damir and \v{S}raml, Matja\v{z}}, year = {2015}, pages = {67-76}, DOI = {10.13167/2015.10.8}, keywords = {microsimulation traffic models, calibration, response of neural networks, traveling time, queue parameters}, journal = {Electronic journal of the Faculty of Civil Engineering Osijek - e-GFOS}, doi = {10.13167/2015.10.8}, volume = {10}, issn = {1847-8948}, title = {Analysis of neural network responses in calibration of microsimulation traffic model}, keyword = {microsimulation traffic models, calibration, response of neural networks, traveling time, queue parameters} }

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Emerging Sources Citation Index (ESCI)


Uključenost u ostale bibliografske baze podataka::


  • CAB Abstracts
  • INSPEC


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