Toward Predicting Stay Time for Private Car Users: A RNN-NALU Approach
Author:
Affiliation:
1. College of Computer Science and Electronic Engineering, Hunan University, Hunan, China
2. Department of Computer Science, Institute of Transportation Studies, University of California, Irvine, CA, USA
3. Zhejiang Lab, Hangzhou, China
Funder
National Natural Science Foundation of China
Humanities and Social Sciences Foundation of Ministry of Education
Key R&D Project of Hunan Province of China
Hunan Natural Science Foundation of China
Funding Project of Zhejiang Lab
Guangming Laboratory
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/25/9805757/09749846.pdf?arnumber=9749846
Reference56 articles.
1. Predicting Stay Time of Mobile Users With Contextual Information
2. Exploring Human Stay Time Patterns from Mobile Phone Data
3. Smartphones as an integrated platform for monitoring driver behaviour: The role of sensor fusion and connectivity
4. Driving safety efficiency benchmarking using smartphone data
5. Hybrid of discrete wavelet transform and adaptive neuro fuzzy inference system for overall driving behavior recognition
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