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Reseach Article

Passenger Travel behavior Model in Railway Network Simulation

by Kulkarni Gauri Ramakant, B. M. Patil
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 163 - Number 2
Year of Publication: 2017
Authors: Kulkarni Gauri Ramakant, B. M. Patil
10.5120/ijca2017913477

Kulkarni Gauri Ramakant, B. M. Patil . Passenger Travel behavior Model in Railway Network Simulation. International Journal of Computer Applications. 163, 2 ( Apr 2017), 36-39. DOI=10.5120/ijca2017913477

@article{ 10.5120/ijca2017913477,
author = { Kulkarni Gauri Ramakant, B. M. Patil },
title = { Passenger Travel behavior Model in Railway Network Simulation },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2017 },
volume = { 163 },
number = { 2 },
month = { Apr },
year = { 2017 },
issn = { 0975-8887 },
pages = { 36-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume163/number2/27371-2017913477/ },
doi = { 10.5120/ijca2017913477 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:09:06.928988+05:30
%A Kulkarni Gauri Ramakant
%A B. M. Patil
%T Passenger Travel behavior Model in Railway Network Simulation
%J International Journal of Computer Applications
%@ 0975-8887
%V 163
%N 2
%P 36-39
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

People usually travel to the same destination and same purpose together with the other people in groups.Inferring the travel purpose of passenger groups help us to better understand passengers and bring meaningful changes for personalized travel service.First we construct cotravel network by extracting social relations between passengers from their historical travel records that are available in passenger information system.We generate series of sophisticated features for each passenger group and use the overlapping relation between passenger groups to capture relations.At last we collectively infer the labels of all the groups in iterative way.

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Index Terms

Computer Science
Information Sciences

Keywords

Collective inference cotravel networks iterative classification.