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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 // Lecture Notes in Computer Science book series (LNCS, volume 11620) / Sanjay Misra ; Osvaldo Gervasi ; Beniamino Murgante ; Elena Stankova ; Vladimir Korkhov ; Carmelo Torre ; Ana Maria A.C. Rocha ; David Taniar ; Bernady O. Apduhan ; Eufemia Tarantino (ur.).
Berlin: Springer International Publishing, 2019. str. 3-11 doi:10.1007/978-3-030-24296-1_1


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
Poglavlja u knjigama, znanstveni

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

Urednik/ci
Sanjay Misra ; Osvaldo Gervasi ; Beniamino Murgante ; Elena Stankova ; Vladimir Korkhov ; Carmelo Torre ; Ana Maria A.C. Rocha ; David Taniar ; Bernady O. Apduhan ; Eufemia Tarantino

Izdavač
Springer International Publishing

Grad
Berlin

Godina
2019

Raspon stranica
3-11

ISBN
978-3-030-24295-4

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


Profili:

Avatar Url Sadko Mandžuka (autor)

Avatar Url Marko Šoštarić (autor)

Citiraj ovu publikaciju

Vidović, Krešimir; Mandžuka, Sadko; Šoštarić, Marko
Expert System for Urban Multimodal Mobility Estimation Based on Information from Public Mobile Network // Lecture Notes in Computer Science book series (LNCS, volume 11620) / Sanjay Misra ; Osvaldo Gervasi ; Beniamino Murgante ; Elena Stankova ; Vladimir Korkhov ; Carmelo Torre ; Ana Maria A.C. Rocha ; David Taniar ; Bernady O. Apduhan ; Eufemia Tarantino (ur.).
Berlin: Springer International Publishing, 2019. str. 3-11 doi:10.1007/978-3-030-24296-1_1
Vidović, K., Mandžuka, S. & Šoštarić, M. (2019) Expert System for Urban Multimodal Mobility Estimation Based on Information from Public Mobile Network. U: Sanjay Misra, Osvaldo Gervasi, Beniamino Murgante, Elena Stankova, Vladimir Korkhov, Carmelo Torre, Ana Maria A.C. Rocha, David Taniar, Bernady O. Apduhan & Eufemia Tarantino (ur.) Lecture Notes in Computer Science book series (LNCS, volume 11620). Berlin, Springer International Publishing, str. 3-11 doi:10.1007/978-3-030-24296-1_1.
@inbook{inbook, 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 International Publishing}, publisherplace = {Berlin} }

Časopis indeksira:


  • Scopus


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