TY - JOUR
T1 - 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
AU - Yang, Jianfeng
AU - Xiao, Heye
AU - Li, Liang
AU - Bai, Junqiang
AU - Dong, Weihao
N1 - Publisher Copyright:
© 2022 Chinese Institute of Electronics. All rights reserved.
PY - 2022/8
Y1 - 2022/8
N2 - 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.
AB - 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.
KW - expert reliability
KW - fuzzy clustering
KW - modular unmanned aerial vehicle (UAV)
KW - module partition method
KW - network hierarchy structure
KW - particle swarm optimization (PSO) algorithm
UR - http://www.scopus.com/inward/record.url?scp=85139565583&partnerID=8YFLogxK
U2 - 10.12305/j.issn.1001-506X.2022.08.18
DO - 10.12305/j.issn.1001-506X.2022.08.18
M3 - 文章
AN - SCOPUS:85139565583
SN - 1001-506X
VL - 44
SP - 2530
EP - 2539
JO - Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
JF - Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
IS - 8
ER -