The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computer Vision Conference (CVC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2023.0140482
PDF

Deep Learning Localization Algorithm Integrating Attention Mechanism in Database Information Query

Author 1: Yang Li
Author 2: Xianghui Hui
Author 3: Xiaolei Wang
Author 4: Fei Yin

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 4, 2023.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: This study aims to solve the problems of traditional indoor car search positioning technology in terms of positioning accuracy and functionality. Based on database technology and deep learning technology, an LSTM model with attention mechanism was established. This model can simultaneously extract temporal and spatial features, and use attention mechanism for feature importance recognition. The entire positioning model has been designed as a triple functional entrance that includes positioning, car storage, and reverse car search, enhancing the user's coherent experience. The data results show that the root mean square error of the LSTM (Attention) model designed in the study is 0.216, and the variance is 0.092. Among similar positioning models, the index value is the smallest, while the CDF line rises the fastest and the maximum value is the highest. The research conclusion indicates that the LSTM (Attention) indoor positioning model designed in this study has better computational performance and can help users achieve more accurate positioning and vehicle navigation.

Keywords: LSTM; attention mechanism; positioning; database

Yang Li, Xianghui Hui, Xiaolei Wang and Fei Yin, “Deep Learning Localization Algorithm Integrating Attention Mechanism in Database Information Query” International Journal of Advanced Computer Science and Applications(IJACSA), 14(4), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140482

@article{Li2023,
title = {Deep Learning Localization Algorithm Integrating Attention Mechanism in Database Information Query},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140482},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140482},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {4},
author = {Yang Li and Xianghui Hui and Xiaolei Wang and Fei Yin}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Computer Vision Conference
  • Healthcare Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org