Research on Ground Air Defense Equipment Deployment Technology Based on Unsupervised Artificial Bee Colony Algorithm

QING Chaojin; ZHAO Guiyi; HE Linsi; ZHANG Yinjie; WEI Maogang; LIU Tian

doi:10.15892/j.cnki.djzdxb.2025.04.007

Journal of Projectiles, Rockets, Missiles and Guidance >

2025 , Vol. 45 >Issue 4: 499 - 509

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2025.04.007

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Research on Ground Air Defense Equipment Deployment Technology Based on Unsupervised Artificial Bee Colony Algorithm

QING Chaojin ^,¹ ,
ZHAO Guiyi ¹ ,
HE Linsi ¹ ,
ZHANG Yinjie ¹ ,
WEI Maogang ¹ ,
LIU Tian ²

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¹ School of Electrical Engineering and Electronic Information, Xihua University, Chengdu 610039, Sichuan, China
² The 10th Research Institute of China Electronics Technology Group Corporation, Chengdu 610036, Sichuan, China

Received date: 2024-07-21

Online published: 2025-09-22

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Abstract

To tackle the challenges of slow deployment speed, inadequate rationality, and suboptimal air defense effectiveness associated with ground-based air defense systems, a novel solution is proposed involving an artificial bee colony (ABC) algorithm integrated with K-means clustering. This innovative method aims to enhance the deployment efficiency and effectiveness of air defense equipment by prioritizing air defense effectiveness as the key evaluation criterion. The approach begins with the analysis of digital elevation model (DEM) data for the deployment area. Using the K-means clustering algorithm, this data is categorized based on critical geographical features such as elevation, slope, and aspect. The clustering process helps in identifying and filtering the most suitable regions within the deployment area. Following this initial classification, the ABC algorithm is employed to perform iterative searches and optimizations within the filtered regions. The iterative process continues until an optimal deployment scheme is generated. This deployment plan is then validated and refined using prior information to ensure its practical applicability and high effectiveness. The primary goal of this methodology is to utilize K-means clustering for preliminary area classification, followed by iterative optimization through the ABC algorithm, to create deployment strategies that offer superior air defense effectiveness. The simulation results show that the research method can generate a deployment scheme with an air defense efficiency of 0.978 1 after 262 iterations within a given deployment area, while the deployment schemes generated by classical swarm intelligence algorithms have air defense efficiencies around 0.960 0 and require more than 400 iterations to converge, demonstrating the real-time nature of the research method; In addition, the deployment plans generated by the research methods can achieve complete coverage of the defense targets, while the deployment plans generated by classical swarm intelligence optimization algorithms may have air defense blind spots, reflecting the rationality of the research methods.

Key words： ground air defense; equipment deployment; K-means; artificial bee colony algorithm; air defense effectiveness

Cite this article

QING Chaojin , ZHAO Guiyi , HE Linsi , ZHANG Yinjie , WEI Maogang , LIU Tian . Research on Ground Air Defense Equipment Deployment Technology Based on Unsupervised Artificial Bee Colony Algorithm[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2025 , 45(4) : 499 -509 . DOI: 10.15892/j.cnki.djzdxb.2025.04.007

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