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

Future of Information and Communication Conference (FICC)

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

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

Future Technologies Conference (FTC)

  • 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.2024.0150966
PDF

Multimedia Network Data Fusion System Integrating SSA and Reinforcement Learning

Author 1: Fangrui Li

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 9, 2024.

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

Abstract: To improve the performance and efficiency of multimedia network data fusion system, this study proposes an improved sparrow search algorithm on the ground of reinforcement learning algorithm and sparrow search algorithm, and improves the multimedia network data fusion model on the ground of this algorithm. A performance comparison experiment was conducted on the improved sparrow search algorithm, and it was found that the algorithm entered a convergence state after 380 iterations in a unimodal function. Its time consumption is lower than other comparison algorithms, and it has not fallen into the local optimal situation after 500 iterations in the multimodal benchmark function. Its performance is significantly superior to other comparison algorithms. Moreover, the study conducted relevant experiments on the multimedia network data fusion model and found that the F1 value output by the model was 0.37, with an accuracy of 92.4%, which is higher than other data fusion models. And the mean square error of this model reaches 0.52, and the processing time is 0.1 seconds, which is lower than other comparative data fusion models. The quality of output data and data processing efficiency of this model are better. The relevant outcomes demonstrate that the improved sparrow search algorithm possesses good global search and convergence performance. And the improved multimedia network data fusion model has better accuracy and efficiency, and has good practical application value. This study can provide reference and reference for multimedia network data fusion systems.

Keywords: Sparrow search algorithm; reinforcement learning; multimedia network; data fusion; performance improvement

Fangrui Li, “Multimedia Network Data Fusion System Integrating SSA and Reinforcement Learning” International Journal of Advanced Computer Science and Applications(IJACSA), 15(9), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0150966

@article{Li2024,
title = {Multimedia Network Data Fusion System Integrating SSA and Reinforcement Learning},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150966},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150966},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {9},
author = {Fangrui Li}
}



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
  • Future Technologies Conference
  • Communication 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