標題: Transportation Type Identification by using Machine Learning Algorithms with Cellular Information
作者: Lin, Yi-Hao
Chen, Jyh-Cheng
Lin, Chih-Yu
Su, Bo-Yue
Lee, Pei-Yu
資訊工程學系
Department of Computer Science
關鍵字: Transportation Type Identification;Machine Learning;Cellular Information;Classification;5G
公開日期: 1-Jan-2019
摘要: It is crucial for future 5G networks to intelligently understand how users move so that the networks can allocate different resources efficiently. In this paper, we try to find practical features to identify four common types of motorized transportations, including High-Speed Rail (HSR), subway, railway, and highway. We propose a system architecture that can provide accurate, real-time, and adaptive solution by using cellular information only. Because we do not use GPS as that in most of the prior studies, we can reduce energy consumption, size of log data, and computational time. Around 500-hour data are collected for performance evaluation. Experimental results confirm the effectiveness of the proposed algorithm, which can improve well-known machine learning algorithms to approximately 98% classification accuracy. The results also show that battery consumption can be reduced about 37%.
URI: http://hdl.handle.net/11536/153266
ISBN: 978-1-5386-8088-9
ISSN: 1550-3607
期刊: ICC 2019 - 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC)
起始頁: 0
結束頁: 0
Appears in Collections:Conferences Paper