Predicting Future Locations of Moving Objects by Recurrent Mixture Density Network

Accurate and timely location prediction of moving objects is crucial for intelligent transportation systems and traffic management. In recent years, ubiquitous location acquisition technologies have provided the opportunity for mining knowledge from trajectories, making location prediction and real-...

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Bibliographic Details

Published in:	ISPRS International Journal of Geo-Information
Main Authors:	Rui Chen, Mingjian Chen, Wanli Li, Naikun Guo
Format:	Article
Language:	English
Published:	MDPI AG 2020-02-01
Subjects:	location prediction long short-term memory mixture density network trajectory mining
Online Access:	https://www.mdpi.com/2220-9964/9/2/116