App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 8

Prediction and reconstruction method for imitation of bird flock behavior in unmanned aerial vehicle swarms

Chen Qiyang1
He Ming1,2
Han Wei1
Li Sike1
Liu Xiang1
1. College of Command and Control Engineering, Army Engineering University of PLA, Nanjing 210007, China
2. National Key Laboratory of Near-Ground Detection, Beijing 100072, China
DOI: 10.19734/j.issn.1001-3695.2025.12.0519

Abstract

To address the problem that the task execution capability of unmanned aerial vehicle (UAV) swarms decreases and the reconstruction speed becomes slow due to node failures and hostile interference, this paper proposes a bird-flocking-inspired resilient reconstruction method for UAV swarm networks. First, the method constructs the UAV swarm network topology based on a complex network model. Then, for swarm reconnaissance missions, this study innovatively proposes a resilience evaluation metric for UAV swarms. Subsequently, by improving the fixed background value generation strategy in the traditional grey prediction model, the method employs the artificial bee colony (ABC) algorithm to dynamically optimize the background value parameters of the grey prediction model. The predicted information is combined with the consensus order parameter to dynamically adjust the weights of the bird-flocking control, thereby enabling predictive reconstruction of the UAV swarm. Simulation results show that, compared with four mainstream reconstruction algorithms, the proposed method demonstrates advantages in both reconstruction time and reconstruction performance. Compared with the PSO-based benchmark method, the proposed approach reduces the average reconstruction time by 36.3% and improves both reconstruction speed and resilience recovery performance.

Foundation Support

国家自然科学基金项目(62273356)
国家级人才项目(2022-JCJQ-ZQ-001)
国家重点研发计划(2024YFF140140)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.12.0519
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 8

Publish History

[2026-04-22] Accepted Paper

Cite This Article

陈启洋, 何明, 韩伟, 等. 无人机仿鸟群行为的预测重构方法 [J]. 计算机应用研究, 2026, 43 (8). (2026-04-30). https://doi.org/10.19734/j.issn.1001-3695.2025.12.0519. (Chen Qiyang, He Ming, Han Wei, et al. Prediction and reconstruction method for imitation of bird flock behavior in unmanned aerial vehicle swarms [J]. Application Research of Computers, 2026, 43 (8). (2026-04-30). https://doi.org/10.19734/j.issn.1001-3695.2025.12.0519. )

About the Journal

  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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