Aviation material classification research based on consumption volatility clustering analysis

被引：1
作者：
Xue Y. [1 ]
Chen Z. [1 ]
机构：
[1] Navy Aviation University, Yantai
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2019年 / 41卷 / 12期
关键词：
Aviation material classification; Cluster analysis; Consumption volatility; Tolerance to distance ratio;
D O I：
10.3969/j.issn.1001-506X.2019.12.19
中图分类号：
学科分类号：
摘要：
To solve the problem that it is difficult to classify aviation material consumption data, a classification model based on consumption fluctuation clustering analysis is established. Based on the fluctuation of the consumption sequence, the aviation materials are converted into two-dimensional graphs. Due to its short service time and small quantity of aviation material samples, the unsupervised classification algorithm is used to classify the aviation material. Aiming at the limitation of traditional clustering algorithms, a hierarchical partition clustering algorithm is proposed, and the "tolerance to distance ratio" parameter is used to select a good environment for the initial center. The simulation results show that the hierarchical partition clustering algorithm is more stable and efficient. © 2019, Editorial Office of Systems Engineering and Electronics. All right reserved.
引用
收藏
页码：2802 / 2806
页数：4
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