Skip to content
Publish & Distribute
Publishing Solutions
Distribution Solutions
Library Services
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
Journal Matcher
Blog
Contact
Search
English
English
Deutsch
Polski
Español
Français
Italiano
Cart
Home
Journals
Applied Mathematics and Nonlinear Sciences
Volume 9 (2024): Issue 1 (January 2024)
Open Access
Deep Learning-based Knowledge Graph and Digital Twin Relationship Mining and Prediction Modeling
Fangzhou He
Fangzhou He
School of Public Security Information Technology and Intelligence, Criminal Investigation Police University of China
Shenyang, China
Search for this author on
Sciendo
|
Google Scholar
He, Fangzhou
,
Wei Bai
Wei Bai
Intelligent Policing Key Laboratory of Sichuan Province
Luzhou, China
Department of Transportation Management, Sichuan Police College
Luzhou, China
Search for this author on
Sciendo
|
Google Scholar
Bai, Wei
and
Zhiqi Wang
Zhiqi Wang
School of Investigation and Counter-Terrorism, Criminal Investigation Police University of China
Shenyang, China
Search for this author on
Sciendo
|
Google Scholar
Wang, Zhiqi
Jul 05, 2024
Applied Mathematics and Nonlinear Sciences
Volume 9 (2024): Issue 1 (January 2024)
About this article
Previous Article
Next Article
Abstract
References
Authors
Articles in this Issue
Preview
PDF
Cite
Share
Download Cover
Published Online:
Jul 05, 2024
Received:
Mar 02, 2024
Accepted:
May 27, 2024
DOI:
https://doi.org/10.2478/amns-2024-1618
Keywords
Digital twin technology
,
Deep learning
,
Knowledge graph
,
Attention mechanism
,
TransE model
© 2024 Fangzhou He, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.