Clustering as an EDA method: the case of pedestrian directional flow behavior.

Given the data of pedestrian trajectories in NTXY format, three clustering methods of K Means, Expectation Maximization (EM) and Affinity Propagation were utilized as Exploratory Data Analysis to find the pattern of pedestrian directional flow behavior. The analysis begins without a prior notion reg...

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Autores principales:	Kardi Teknomo, Ma. Regina E. Estuar
Formato:	article
Lenguaje:	EN ES
Publicado:	Universidad de San Buenaventura 2010
Materias:	Gaussian Mixture directional flow pattern pedestrian behavior trajectory analysis Psychology BF1-990
Acceso en línea:	https://doaj.org/article/da0196e4f7154d3b9d4d573eb04d3ab5
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spelling	oai:doaj.org-article:da0196e4f7154d3b9d4d573eb04d3ab52021-11-25T02:24:06ZClustering as an EDA method: the case of pedestrian directional flow behavior.10.21500/20112084.8202011-20842011-7922https://doaj.org/article/da0196e4f7154d3b9d4d573eb04d3ab52010-06-01T00:00:00Zhttps://revistas.usb.edu.co/index.php/IJPR/article/view/820https://doaj.org/toc/2011-2084https://doaj.org/toc/2011-7922Given the data of pedestrian trajectories in NTXY format, three clustering methods of K Means, Expectation Maximization (EM) and Affinity Propagation were utilized as Exploratory Data Analysis to find the pattern of pedestrian directional flow behavior. The analysis begins without a prior notion regarding the structure of the pattern and it consequentially infers the structure of directional flow pattern. Significant similarities in patterns for both individual and instantaneous walking angles based on EDA method are reported and explained in case studies.Kardi TeknomoMa. Regina E. EstuarUniversidad de San BuenaventuraarticleGaussian Mixturedirectional flow patternpedestrian behaviortrajectory analysisPsychologyBF1-990ENESInternational Journal of Psychological Research, Vol 3, Iss 1 (2010)
institution	DOAJ
collection	DOAJ
language	EN ES
topic	Gaussian Mixture directional flow pattern pedestrian behavior trajectory analysis Psychology BF1-990
spellingShingle	Gaussian Mixture directional flow pattern pedestrian behavior trajectory analysis Psychology BF1-990 Kardi Teknomo Ma. Regina E. Estuar Clustering as an EDA method: the case of pedestrian directional flow behavior.
description	Given the data of pedestrian trajectories in NTXY format, three clustering methods of K Means, Expectation Maximization (EM) and Affinity Propagation were utilized as Exploratory Data Analysis to find the pattern of pedestrian directional flow behavior. The analysis begins without a prior notion regarding the structure of the pattern and it consequentially infers the structure of directional flow pattern. Significant similarities in patterns for both individual and instantaneous walking angles based on EDA method are reported and explained in case studies.
format	article
author	Kardi Teknomo Ma. Regina E. Estuar
author_facet	Kardi Teknomo Ma. Regina E. Estuar
author_sort	Kardi Teknomo
title	Clustering as an EDA method: the case of pedestrian directional flow behavior.
title_short	Clustering as an EDA method: the case of pedestrian directional flow behavior.
title_full	Clustering as an EDA method: the case of pedestrian directional flow behavior.
title_fullStr	Clustering as an EDA method: the case of pedestrian directional flow behavior.
title_full_unstemmed	Clustering as an EDA method: the case of pedestrian directional flow behavior.
title_sort	clustering as an eda method: the case of pedestrian directional flow behavior.
publisher	Universidad de San Buenaventura
publishDate	2010
url	https://doaj.org/article/da0196e4f7154d3b9d4d573eb04d3ab5
work_keys_str_mv	AT karditeknomo clusteringasanedamethodthecaseofpedestriandirectionalflowbehavior AT mareginaeestuar clusteringasanedamethodthecaseofpedestriandirectionalflowbehavior
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Clustering as an EDA method: the case of pedestrian directional flow behavior.

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