bibtype C - Conference Paper (international conference)
ARLID 0507178
utime 20240111141022.0
mtime 20190801235959.9
SCOPUS 85073104783
title (primary) (eng) Modeling of passenger demand using mixture of Poisson components
specification
page_count 8 s.
media_type C
serial
ARLID cav_un_epca*0507177
ISBN 978-989-758-380-3
title Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2019)
part_title Volume 1
page_num 617-624
publisher
place Setubal
name SCITEPRESS
year 2019
editor
name1 Gusikhin
name2 Oleg
editor
name1 Madani
name2 Kurosh
editor
name1 Zaytoon
name2 Janan
keyword mixture estimation
keyword Poisson components
keyword Passenger demand
author (primary)
ARLID cav_un_auth*0349960
name1 Petrouš
name2 Matej
institution UTIA-B
full_dept (cz) Zpracování signálů
full_dept (eng) Department of Signal Processing
department (cz) ZS
department (eng) ZS
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0355927
name1 Suzdaleva
name2 Evženie
institution UTIA-B
full_dept (cz) Zpracování signálů
full_dept Department of Signal Processing
department (cz) ZS
department ZS
full_dept Department of Signal Processing
country RU
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101167
name1 Nagy
name2 Ivan
institution UTIA-B
full_dept (cz) Zpracování signálů
full_dept Department of Signal Processing
department (cz) ZS
department ZS
full_dept Department of Signal Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
source_type pdf
url http://library.utia.cas.cz/separaty/2019/ZS/suzdaleva-0507178.pdf
cas_special
project
ARLID cav_un_auth*0351997
project_id 8A17006
agency GA MŠk
country CZ
abstract (eng) The paper deals with the problem of modeling the passenger demand in the tram transportation network. The passenger demand on the individual tram stops is naturally influenced by the number of boarding and disembarking passengers, whose measuring is expensive and therefore they should be modeled and predicted. A mixture of Poisson components with the dynamic pointer estimated by recursive Bayesian estimation algorithms is used to describe the mentioned variables, while their prediction is solved with the help of the Poisson regression. The main contributions of the presented approach are: (i) the model of the number of boarding and disembarking passengers. (ii) the real-time data incorporation into the model. (iii) the recursive estimation algorithm with the normal approximation of the proximity function. The results of experiments with real data and the comparison with theoretical counterparts are demonstrated.
action
ARLID cav_un_auth*0377849
name International Conference on Informatics in Control, Automation and Robotics (ICINCO 2019) /16./
dates 20190729
mrcbC20-s 20190731
place Prague
country CZ
RIV BB
FORD0 10000
FORD1 10100
FORD2 10103
reportyear 2020
num_of_auth 3
presentation_type PR
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0298563
confidential S
arlyear 2019
mrcbU14 85073104783 SCOPUS
mrcbU24 PUBMED
mrcbU34 WOS
mrcbU56 pdf
mrcbU63 cav_un_epca*0507177 Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2019) Volume 1 SCITEPRESS 2019 Setubal 617 624 978-989-758-380-3
mrcbU67 340 Gusikhin Oleg
mrcbU67 340 Madani Kurosh
mrcbU67 340 Zaytoon Janan