@inproceedings{0d067efbe67a4005904d75754036b2cf,
title = "Research on State Evaluation Method of Fire Control System Based on Improved K\_ means Algorithm",
abstract = "- In order to improve the accuracy of tank fire control system state evaluation, a new method based on improved K-means is proposed, which takes a certain type of tank fire control system gyroscope group as the research object. The method of evaluating the gyroscope group state of fire control system based on means clustering algorithm. This method adopts the basic principle of Kmeans algorithm to reduce the subjective factors in the evaluation process. Principal component analysis is used to extract data features, and then the initial clustering center is selected by minimum variance to reduce the randomness of the initial clustering center and improve the accuracy. In view of the lack of data samples, the bootstrap small sample statistical method is integrated. Finally, benchmark sample data and test data are used to verify the feasibility and accuracy of the method.",
keywords = "Bootstrap algorithm, Gyroscope, Kmeans algorithm, State evaluation",
author = "Li Yingshun and Zhang Guoying and Yi Xiaojian",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2021 ; Conference date: 13-08-2021 Through 15-08-2021",
year = "2021",
doi = "10.1109/SDPC52933.2021.9563593",
language = "English",
series = "Proceedings of 2021 IEEE International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "48--53",
editor = "Xuyun Fu and Shengcai Deng and Diego Cabrera and Yongjian Zhang and Zhiqiang Pu",
booktitle = "Proceedings of 2021 IEEE International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2021",
address = "United States",
}