Measuring traffic congestion: An approach based on learning weighted inequality, spread and aggregation indices from comparison data

Gleb Beliakov , Marek Gągolewski , Simon James , Shannon Pace , Nicola Pastorello , Elodie Thilliez , Rajesh Vasa

Abstract

n/a
Author Gleb Beliakov
Gleb Beliakov,,
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, Marek Gągolewski (FMIS / DIE) - [Systems Research Institute (IBS PAN) [Polska Akademia Nauk (PAN)]]
Marek Gągolewski,,
- Department of Integral Equations
- Instytucie Badań Systemowych
, Simon James
Simon James,,
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, Shannon Pace
Shannon Pace,,
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, Nicola Pastorello
Nicola Pastorello,,
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, Elodie Thilliez
Elodie Thilliez,,
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, Rajesh Vasa
Rajesh Vasa,,
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Journal seriesApplied Soft Computing, ISSN 1568-4946, (A 40 pkt)
Issue year2018
Vol67
Pages910-919
Publication size in sheets0.5
Keywords in Englishaggregation functions; inequality indices; spread measures; learning weights; congestion; traffic analysis Science & Technology Technology Computer Science, Artificial Intelligence Computer Science, Interdisciplinary Applications; Computer Science; PREDICTION; DIVERSITY
ASJC Classification1712 Software
DOIDOI:10.1016/j.asoc.2017.07.014
URL http://dro.deakin.edu.au/view/DU:30104229
Languageen angielski
Score (nominal)40
ScoreMinisterial score = 40.0, 15-05-2019, ArticleFromJournal
Publication indicators Scopus SNIP (Source Normalised Impact per Paper): 2016 = 2.037; WoS Impact Factor: 2017 = 3.907 (2) - 2017=4.004 (5)
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