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.2018.090312
PDF

Online Incremental Rough Set Learning in Intelligent Traffic System

Author 1: Amal Bentaher
Author 2: Yasser Fouad
Author 3: Khaled Mahar

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 3, 2018.

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

Abstract: In the last few years, vehicle to vehicle communication (V2V) technology has been developed to improve the efficiency of traffic communication and road accident avoidance. In this paper, we have proposed a model for online rough sets learning vehicle to vehicle communication algorithm. This model is an incremental learning method, which can learn data object-by-object or class-by-class. This paper proposed a new rules generation for vehicle data classifying in collaborative environments. ROSETTA tool is applied to verify the reliability of the generated results. The experiments show that the online rough sets based algorithm for vehicle data classifying is suitable to be executed in the communication of traffic environments. The implementation of this model on the objectives’ (cars’) rules that define parameters for the determination of the value of communication, and for reducing the decision rules that leads to the estimation of their optimal value. The confusion matrix is used to assess the performance of the chosen model and classes (Yes or No). The experimental results show the overall accuracy (predicted and actual) of the proposed model. The results show the strength of the online learning model against offline models and demonstrate the importance of the accuracy and adaptability of the incremental learning in improving the prediction ability.

Keywords: Vehicle to vehicle communication; online learning; rough sets theory; intelligent traffic system

Amal Bentaher , Yasser Fouad and Khaled Mahar, “Online Incremental Rough Set Learning in Intelligent Traffic System” International Journal of Advanced Computer Science and Applications(IJACSA), 9(3), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090312

@article{2018,
title = {Online Incremental Rough Set Learning in Intelligent Traffic System},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090312},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090312},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {3},
author = {Amal Bentaher and Yasser Fouad and Khaled Mahar}
}



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