Transportation Mode Detection Based on Permutation Entropy and Extreme Learning Machine
Joint Authors
Zhang, Lei
Liu, LeiJun
Bao, SuNing
Qiang, MengTing
Zou, XiaoMei
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-12-09
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
With the increasing prevalence of GPS devices and mobile phones, transportation mode detection based on GPS data has been a hot topic in GPS trajectory data analysis.
Transportation modes such as walking, driving, bus, and taxi denote an important characteristic of the mobile user.
Longitude, latitude, speed, acceleration, and direction are usually used as features in transportation mode detection.
In this paper, first, we explore the possibility of using Permutation Entropy (PE) of speed, a measure of complexity and uncertainty of GPS trajectory segment, as a feature for transportation mode detection.
Second, we employ Extreme Learning Machine (ELM) to distinguish GPS trajectory segments of different transportation.
Finally, to evaluate the performance of the proposed method, we make experiments on GeoLife dataset.
Experiments results show that we can get more than 50% accuracy when only using PE as a feature to characterize trajectory sequence.
PE can indeed be effectively used to detect transportation mode from GPS trajectory.
The proposed method has much better accuracy and faster running time than the methods based on the other features and SVM classifier.
American Psychological Association (APA)
Zhang, Lei& Liu, LeiJun& Bao, SuNing& Qiang, MengTing& Zou, XiaoMei. 2015. Transportation Mode Detection Based on Permutation Entropy and Extreme Learning Machine. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1075124
Modern Language Association (MLA)
Zhang, Lei…[et al.]. Transportation Mode Detection Based on Permutation Entropy and Extreme Learning Machine. Mathematical Problems in Engineering No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1075124
American Medical Association (AMA)
Zhang, Lei& Liu, LeiJun& Bao, SuNing& Qiang, MengTing& Zou, XiaoMei. Transportation Mode Detection Based on Permutation Entropy and Extreme Learning Machine. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1075124
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1075124