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Article Open Access April 22, 2022

Particle Swarm Network Design for UCAV Intelligence System Path Planning

Sheharyar Khan 1,* and Sohrab Khan 2
1
School of Software, Northwestren Polytechnical University, Xian, China
2
School of Computer Science, University of Haripur, Haripur, Pakistan
Publihed in: Current Research in Public Health (Volume 1, Issue 1, 2022)
Page(s): 1-8
DOI: 10.31586/ujcsc.2022.267
Received
March 13, 2022
Revised
April 12, 2022
Accepted
April 20, 2022
Published
April 22, 2022
Keywords
Particle Swarm; Artificial Neural network (ANN); unmanned combat aerial vehicle (UCAV)
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright: Copyright © The Author(s), 2022. Published by Scientific Publications
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Cite This Article

APA Style
Khan, S. , & Khan, S. (2022). Particle Swarm Network Design for UCAV Intelligence System Path Planning. Current Research in Public Health, 1(1), 1-8. https://doi.org/10.31586/ujcsc.2022.267
ACS Style
Khan, S. ; Khan, S. Particle Swarm Network Design for UCAV Intelligence System Path Planning. Current Research in Public Health 2022 1(1), 1-8. https://doi.org/10.31586/ujcsc.2022.267
Chicago/Turabian Style
Khan, Sheharyar, and Sohrab Khan. 2022. "Particle Swarm Network Design for UCAV Intelligence System Path Planning". Current Research in Public Health 1, no. 1: 1-8. https://doi.org/10.31586/ujcsc.2022.267
AMA Style
Khan S, Khan S. Particle Swarm Network Design for UCAV Intelligence System Path Planning. Current Research in Public Health. 2022; 1(1):1-8. https://doi.org/10.31586/ujcsc.2022.267 
@Article{crph267,
AUTHOR = {Khan, Sheharyar and Khan, Sohrab},
TITLE = {Particle Swarm Network Design for UCAV Intelligence System Path Planning},
JOURNAL = {Current Research in Public Health},
VOLUME = {1},
YEAR = {2022},
NUMBER = {1},
PAGES = {1-8},
URL = {https://www.scipublications.com/journal/index.php/UJCSC/article/view/267},
ISSN = {2831-5162},
DOI = {10.31586/ujcsc.2022.267},
ABSTRACT = {In military battle, the unmanned combat aerial vehicle (UCAV) plays a critical role. The UCAV avoids the fatal military zone as well as radars. If there is just a narrow path between the defensive areas, it is dan-gerous. It chooses the quickest and safest path. The balance evolution technique is used to improve the path planning of UCAV in this study, which results in a novel artificial bee colony. To regulate the position of a swarm of UCAVs, a particle swarm network is used to communicate between the UCAVs in the swarm. According to simulation data, the particle swarm network technique is more efficient than the ABC ap-proach. The intelligence system is taught via an artificial neural network.},
}
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TY  - JOUR
AU  - Khan, Sheharyar
AU  - Khan, Sohrab
TI  - Particle Swarm Network Design for UCAV Intelligence System Path Planning
T2  - Current Research in Public Health
PY  - 2022
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UR  - https://www.scipublications.com/journal/index.php/UJCSC/article/view/267
AB  - In military battle, the unmanned combat aerial vehicle (UCAV) plays a critical role. The UCAV avoids the fatal military zone as well as radars. If there is just a narrow path between the defensive areas, it is dan-gerous. It chooses the quickest and safest path. The balance evolution technique is used to improve the path planning of UCAV in this study, which results in a novel artificial bee colony. To regulate the position of a swarm of UCAVs, a particle swarm network is used to communicate between the UCAVs in the swarm. According to simulation data, the particle swarm network technique is more efficient than the ABC ap-proach. The intelligence system is taught via an artificial neural network.
DO  - Particle Swarm Network Design for UCAV Intelligence System Path Planning
TI  - 10.31586/ujcsc.2022.267
ER  -