Login
Register
Reset Password
Publish & Distribute
Publishing Solutions
Distribution Solutions
Subjects
Architecture and Design
Arts
Business and Economics
Chemistry
Classical and Ancient Near Eastern Studies
Computer Sciences
Cultural Studies
Engineering
General Interest
Geosciences
History
Industrial Chemistry
Jewish Studies
Law
Library and Information Science, Book Studies
Life Sciences
Linguistics and Semiotics
Literary Studies
Materials Sciences
Mathematics
Medicine
Music
Pharmacy
Philosophy
Physics
Social Sciences
Sports and Recreation
Theology and Religion
Publications
Journals
Books
Proceedings
Publishers
Blog
Contact
Search
EUR
USD
GBP
English
English
Deutsch
Polski
Español
Français
Italiano
Cart
Home
Journals
Cybernetics and Information Technologies
Volume 22 (2022): Issue 2 (June 2022)
Open Access
An Augmented UCAL Model for Predicting Trajectory and Location
Nesrine Kadri
Nesrine Kadri
,
Ameni Ellouze
Ameni Ellouze
,
Sameh Turki
Sameh Turki
and
Mohamed Ksantini
Mohamed Ksantini
| Jun 23, 2022
Cybernetics and Information Technologies
Volume 22 (2022): Issue 2 (June 2022)
About this article
Previous Article
Next Article
Abstract
References
Authors
Articles in this Issue
Preview
PDF
Cite
Share
Published Online:
Jun 23, 2022
Page range:
114 - 124
Received:
Jan 24, 2022
Accepted:
Mar 29, 2022
DOI:
https://doi.org/10.2478/cait-2022-0020
Keywords
Deep learning
,
LSTM
,
attention mechanism
,
human mobility prediction location
,
trajectory
© 2022 Nesrine Kadri et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Nesrine Kadri
CEM Lab, ENIS, University of Sfax
Tunisia
ISITCom University of Sousse
Tunisia
Ameni Ellouze
CEM Lab, ENIS, University of Sfax
Tunisia
ISIMG, University of Gabes,
Tunisia
Sameh Turki
MIRACL Lab, FSEGS, University of Sfax
Tunisia
Mohamed Ksantini
CEM Lab, ENIS, University of Sfax
Tunisia