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App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 2

Synergistic path planning for shipborne multi-UAV systems based on fusion algorithm of deep learning and dynamic ant colony

Huang Zijian
Wang Xiuhong
Yuan Xuefeng
School of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou Henan 450015, China
DOI: 10.19734/j.issn.1001-3695.2025.06.0212

Abstract

To improve the path optimization capability and scheduling efficiency of shipborne multi-UAV systems in dynamic port environments, a path planning method based on a deep learning–dynamic ant colony optimization (DL-DACO) algorithm was proposed. First, considering the complexity of cooperative movements among the carrier ship, target vessels, and UAVs in dynamic environments, an integer programming model for path optimization was constructed, incorporating a dynamic mobile base station and monitoring time window constraints. At the algorithmic level, deep learning was used to adaptively design the parameter combinations of the pheromone importance factor and heuristic importance factor, a dynamic distance matrix was introduced to replace the static one, and a nonlinear adjustment strategy was employed to optimize the pheromone evaporation mechanism. Experimental results showed that, compared with the traditional fixed-base strategy, the proposed method reduced the total monitoring time by 17.77%, and achieved reductions of 3.87% and 4.76% compared with existing algorithms. The results indicate that the proposed model and fusion algorithm effectively improve the efficiency of UAV-based pollutant monitoring and enhance the cooperative path planning capability of shipborne multi-UAV systems.

Foundation Support

国家自然科学基金资助项目(72304253)
河南省科技攻关项目(222102210329)
河南省教育厅人文社科一般项目(2024-ZZJH-040)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.06.0212
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 2

Publish History

[2025-10-27] Accepted Paper

Cite This Article

黄子健, 王秀红, 袁雪峰. 基于深度学习-动态蚁群融合算法的船载多无人机协同路径规划 [J]. 计算机应用研究, 2026, 43 (2). (2025-11-04). https://doi.org/10.19734/j.issn.1001-3695.2025.06.0212. (Huang Zijian, Wang Xiuhong, Yuan Xuefeng. Synergistic path planning for shipborne multi-UAV systems based on fusion algorithm of deep learning and dynamic ant colony [J]. Application Research of Computers, 2026, 43 (2). (2025-11-04). https://doi.org/10.19734/j.issn.1001-3695.2025.06.0212. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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  • The Second National Periodical Award 100 Key Journals
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  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
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