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Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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Sensors and Materials
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
(proofreading and recording)
MYU K.K.
(translation service)
The Art of Writing Scientific Papers
(How to write scientific papers)
(Japanese Only)
Sensors and Materials, Volume 31, Number 11(4) (2019)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 3827-3834
S&M2052 Research Paper of Special Issue https://doi.org/10.18494/SAM.2019.2565 Published: November 30, 2019 Anomaly Detection in Taxi Flow by a Projection Method [PDF] Myeong-Hun Jeong, Seung-Bae Jeon, Sangjun Park, and Sanggu Kang (Received August 25, 2019; Accepted October 16, 2019) Keywords: trajectory outliers, projection method, trajectory data mining, outlier detection
The prevalence of location-aware devices has propelled studies on the analysis of movement data. In this study, we investigated anomaly detection in taxi trajectories. A projection method was used to detect trajectory outliers. This is a robust statistical method and considers two dimensions of data simultaneously—distance and time. The experimental data included taxi movements in Seoul City and New York City. The results were compared with those of an alternative method, the Mahalanobis distance approach. The findings were observed to be similar. The proposed method can be used to improve the services of taxis and buses.
Corresponding author: Sangjun Park  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Myeong-Hun Jeong, Seung-Bae Jeon, Sangjun Park, and Sanggu Kang, Anomaly Detection in Taxi Flow by a Projection Method, Sens. Mater., Vol. 31, No. 11, 2019, p. 3827-3834. |
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