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...

Full description

Saved in:

Bibliographic Details
Main Authors:	Estuar, Ma. Regina Justina E, Teknomo, Kardi
Format:	text
Published:	Archīum Ateneo 2010
Subjects:	Gaussian Mixture directional flow pattern pedestrian behavior trajectory analysis Computer Sciences
Online Access:	https://archium.ateneo.edu/discs-faculty-pubs/197 https://revistas.usb.edu.co/index.php/IJPR/article/view/820
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Ateneo De Manila University

id	ph-ateneo-arc.discs-faculty-pubs-1196
record_format	eprints
spelling	ph-ateneo-arc.discs-faculty-pubs-11962020-09-09T06:51:14Z Clustering as an EDA method: the case of pedestrian directional flow behavior Estuar, Ma. Regina Justina E Teknomo, Kardi 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. 2010-01-01T08:00:00Z text https://archium.ateneo.edu/discs-faculty-pubs/197 https://revistas.usb.edu.co/index.php/IJPR/article/view/820 Department of Information Systems & Computer Science Faculty Publications Archīum Ateneo Gaussian Mixture directional flow pattern pedestrian behavior trajectory analysis Computer Sciences
institution	Ateneo De Manila University
building	Ateneo De Manila University Library
country	Philippines
collection	archium.Ateneo Institutional Repository
topic	Gaussian Mixture directional flow pattern pedestrian behavior trajectory analysis Computer Sciences
spellingShingle	Gaussian Mixture directional flow pattern pedestrian behavior trajectory analysis Computer Sciences Estuar, Ma. Regina Justina E Teknomo, Kardi 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	text
author	Estuar, Ma. Regina Justina E Teknomo, Kardi
author_facet	Estuar, Ma. Regina Justina E Teknomo, Kardi
author_sort	Estuar, Ma. Regina Justina E
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	Archīum Ateneo
publishDate	2010
url	https://archium.ateneo.edu/discs-faculty-pubs/197 https://revistas.usb.edu.co/index.php/IJPR/article/view/820
_version_	1681506837064581120

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

Similar Items