Abstract：Aiming at the difficulty of screening abnormal data while analyzing the test data of tactical missile, this paper proposes a novel test data analysis algorithm based on improved Kmeans clustering. By choosing the optimal initial cluster center and rejecting abnormal data, Kmeans clustering method is improved in respect of accuracy and efficiency. The case study indicates that the proposed test data analysis algorithm can complete screening of test data with high efficiency while ensuring certain accuracy, and can assist tactical missile data analysis to a certain extent.
黄伟恺, 马行, 刘进, 李宇平, 郑丹力. 基于改进K均值聚类的战术导弹试验数据分析[J]. 空天防御, 2019, 2(4): 69-74.
HUANG Weikai, MA Xing, LIU Jin, LI Yuping, ZHENG Danli. Analysis of Tactical Missile Test Data Based on Improved K Means Clustering. Air & Space Defense, 2019, 2(4): 69-74.
