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基于模糊聚类和专家评分机制的无人机多层次模块划分方法

  • Jianfeng Yang
  • , Heye Xiao
  • , Liang Li
  • , Junqiang Bai
  • , Weihao Dong
  • Northwestern Polytechnical University Xian
  • Unit 95889 of Pla

科研成果: 期刊稿件文章同行评审

7 引用 (Scopus)

摘要

Based on the multi-level progressive module partition architecture of preliminary partition-comprehensive evaluation-precision partition, this paper provides a credible and effective method for module partition in modular unmanned aerial vehicle (UAV) design. In order to improve the credibility of the results of module partition, a scoring mechanism using expert reliability is introduced in the evaluation of module partition indicators. A multi-level module partition method is presented by applying fuzzy clustering and expert scoring mechanism. Taking the one-time and reusable UAVs as examples, the proposed module partition method is adopted to cluster the components and form a module partition scheme. Through the results of the module partition, it can be seen that the proposed method can provide a reliable module partition scheme and satisfy their application characteristics for different kinds of UAVs. Therefore, the rationality and effectiveness of the method is further verified.

投稿的翻译标题Multi-level module partition method of UAV based on fuzzy clustering and expert scoring mechanism
源语言繁体中文
页(从-至)2530-2539
页数10
期刊Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
44
8
DOI
出版状态已出版 - 8月 2022

关键词

  • expert reliability
  • fuzzy clustering
  • modular unmanned aerial vehicle (UAV)
  • module partition method
  • network hierarchy structure
  • particle swarm optimization (PSO) algorithm

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