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Pregled bibliografske jedinice broj: 1045506

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.).
Sankt Peterburg, Ruska Federacija: Springer, 2019. str. 3-11 doi:10.1007/978-3-030-24296-1_1 (pozvano predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)

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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
19th International Conference on Computational Science and Its Applications (ICCSA 2019)

Mjesto i datum
Sankt Peterburg, Ruska Federacija, 01.07.2019. - 04.07.2019

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

Napomena
Lecture Notes in Computer Science book series (LNCS, volume 11620)



POVEZANOST RADA

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

Profili:

Avatar Url Marko Šoštarić (autor)

Avatar Url Sadko Mandžuka (autor)

Avatar Url Krešimir Vidović (autor)

Poveznice na cjeloviti tekst rada:

doi

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.).
Sankt Peterburg, Ruska Federacija: 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, O., Murgante, B., Stankova, E., Korkhov, V., 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, author = {Vidovi\'{c}, Kre\v{s}imir and Mand\v{z}uka, Sadko and \v{S}o\v{s}tari\'{c}, Marko}, 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 = {Sankt Peterburg, Ruska Federacija} }
@article{article, author = {Vidovi\'{c}, Kre\v{s}imir and Mand\v{z}uka, Sadko and \v{S}o\v{s}tari\'{c}, Marko}, 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 = {Sankt Peterburg, Ruska Federacija} }

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Conference Proceedings Citation Index - Science (CPCI-S)
  • Scopus

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