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Expert System for Urban Multimodal Mobility Estimation Based on Information from Public Mobile Network


Vidović, Krešimir; Mandžuka, Sadko; Šoštarić, Marko
Expert System for Urban Multimodal Mobility Estimation Based on Information from Public Mobile Network // Computational Science and Its Applications - ICCSA 2019 / Misra, Sanjay ; Gervasi ; Osvaldo ; Murgante, Beniamino ; Stankova, Elena ; Korkhov ; Vladimir ; Torre, Carmelo ; Rocha, Ana Maria A.C. ; Taniar, David ; Apduhan, Bernady O. ; Tarantino, Eufemia (ur.).
Saint Petersburg, Russia: Springer, 2019. str. 3-11 doi:10.1007/978-3-030-24296-1_1 (pozvano predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Expert System for Urban Multimodal Mobility Estimation Based on Information from Public Mobile Network

Autori
Vidović, Krešimir ; Mandžuka, Sadko ; Šoštarić, Marko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Computational Science and Its Applications - ICCSA 2019 / Misra, Sanjay ; Gervasi ; Osvaldo ; Murgante, Beniamino ; Stankova, Elena ; Korkhov ; Vladimir ; Torre, Carmelo ; Rocha, Ana Maria A.C. ; Taniar, David ; Apduhan, Bernady O. ; Tarantino, Eufemia - : Springer, 2019, 3-11

ISBN
978-3-030-24295-4

Skup
Computational Science and Its Applications - ICCSA 2019 - 19th International Conference

Mjesto i datum
Saint Petersburg, Russia, 1-4.7.2019

Vrsta sudjelovanja
Pozvano predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Urban mobility ; Multimodality ; ANFIS ; Mobile communication network ; Call detail record

Sažetak
Paper present new approach of urban multimodal mobility (UMM) estimation using anonymized data from public mobile network (PMN). The data set is derived from Call Data Records database, and urban multimodal mobility indicators were defined and relativized. Usage of indicators relativized values ensures that they can be applied for mobility estimation in all urban environment regardless of their physical differences, with existing public mobile network as single prerequisite. Travel mode classification is based on Adaptive Neuro Fuzzy Inference System (ANFIS) and trained using set of rules that were determined using method of surveying experts in domain of urban mobility. Accurate estimate creates a foundation for improvement of existing end creation of new services in urban mobility. Also, this approach has potential through implementation within advanced applications of Intelligent Transport Systems with the goal to improve travel modal shift, passenger comfort, efficiency of urban transport etc.

Izvorni jezik
Engleski

Znanstvena područja
Tehnologija prometa i transport



POVEZANOST RADA


Ustanove
Ericsson Nikola Tesla d.d.,
Fakultet prometnih znanosti, Zagreb

Citiraj ovu publikaciju

Vidović, Krešimir; Mandžuka, Sadko; Šoštarić, Marko
Expert System for Urban Multimodal Mobility Estimation Based on Information from Public Mobile Network // Computational Science and Its Applications - ICCSA 2019 / Misra, Sanjay ; Gervasi ; Osvaldo ; Murgante, Beniamino ; Stankova, Elena ; Korkhov ; Vladimir ; Torre, Carmelo ; Rocha, Ana Maria A.C. ; Taniar, David ; Apduhan, Bernady O. ; Tarantino, Eufemia (ur.).
Saint Petersburg, Russia: Springer, 2019. str. 3-11 doi:10.1007/978-3-030-24296-1_1 (pozvano predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Vidović, K., Mandžuka, S. & Šoštarić, M. (2019) Expert System for Urban Multimodal Mobility Estimation Based on Information from Public Mobile Network. U: Misra, S., Gervasi, Osvaldo, Murgante, B., Stankova, E., Korkhov, Vladimir, Torre, C., Rocha, A., Taniar, D., Apduhan, B. & Tarantino, E. (ur.)Computational Science and Its Applications - ICCSA 2019 doi:10.1007/978-3-030-24296-1_1.
@article{article, year = {2019}, pages = {3-11}, DOI = {10.1007/978-3-030-24296-1\_1}, keywords = {Urban mobility, Multimodality, ANFIS, Mobile communication network, Call detail record}, doi = {10.1007/978-3-030-24296-1\_1}, isbn = {978-3-030-24295-4}, title = {Expert System for Urban Multimodal Mobility Estimation Based on Information from Public Mobile Network}, keyword = {Urban mobility, Multimodality, ANFIS, Mobile communication network, Call detail record}, publisher = {Springer}, publisherplace = {Saint Petersburg, Russia} }

Časopis indeksira:


  • Scopus


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