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Prioritizing Maintenance of Naval Command and Control System Using Feature Selection

  • Choi, Junhyeong (Dept. of Computer Science and Engineering, Korea National Defense University) ;
  • Kang, Dongsu (Dept. of Computer Science and Engineering, Korea National Defense University)
  • 투고 : 2019.10.10
  • 심사 : 2019.11.05
  • 발행 : 2019.11.29

초록

해군 지휘통제체계는 작전에 매우 중요한 체계이고, 이 체계의 장애는 전쟁 수행에 있어 치명적일 수 있다. 이러한 장애에 대비하기 위하여, 데이터 마이닝 기법 중 하나인 속성 선택(Feature Selection) 기법을 이용한다. 먼저, 해군의 2016년부터 2018년까지의 장애 데이터를 분석한 후, 속성 선택 기법을 이용하여 장애와 가장 연관이 깊은 속성을 도출하고 장애에 대하여 예측한다. 또한, 속성 간의 연관 정도를 이용하여 해군 지휘통제체계의 유지보수 우선순위를 산정하는 방법을 제안한다. 이는 해군 지휘통제체계 유지보수에 있어 효율성과 경제성을 향상시킬 수 있다.

Naval command and control system are very important for operation and their failures can be fatal for warfare. To prepare for these failures, we use feature selection method which is one of the data mining techniques. First, we analyzes failure data set of Navy from 2016 to 2018. And then We derive attributes that are associated with failure and to predict failure using feature selection method. We propose a method for prioritizing maintenance using the degree of association of attributes. This improves the efficiency and economics of command and control system maintenance.

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참고문헌

  1. Haejin Lee, and Dongsu Kang, "A Method of Service Refinement for Network-Centric Operational Environment," Journal of The Korea Society of Computer and Information, Vol. 21, No. 12, pp. 97-105, 2016. DOI: 10.9708/jksci.2016.21.12.097
  2. Kyeongyoun Kwon, Joonseok Joo, Taesik Kim, Jinwoo Oh, and Jihyun Baek, "A Study on Quality Assurance of Embedded Software Source Codes for Weapon Systems by Improving the Reliability Test Process," Journal of The Korean Institute of Information Scientists and Engineers, Vol. 42, No. 7, pp. 860-867, 2015. DOI: 10.5626/JOK.2015.42.7.860
  3. Jihyun Park, and Byoungju Choi, "Analysis on Dynamic Software Defects for Increasing Weapon System Reliability," Journal of The Korea Information Processing Society, Vol. 7, No. 7, pp. 249-258, 2018. DOI: 10.3745/KTSDE.2018.7.7.249
  4. Kyeongyong Kwon, "Considering the defense business properties Embedded SW weapons systems process assessment mode (MND-EAPAM) Development," Defense & Technology, No. 405, 2012.
  5. Ssangyong Communications, "Document of Maintenance Monthly Meeting," 2016-2018.
  6. Junhyeong Choi, and Dongsu Kang, "An Analysis of Naval Command & Control System Failures Using Feature Selection," Journal of the Korea Naval Academy Maritime Institute, Vol. Special Edition, pp. 121-126, 2019.
  7. Navy Headquarters, "Navy Glossary," p. 549, 2011.
  8. Navy Headquarters, "KNCCS Guidebook," pp. 3-4, 2017.
  9. Navy Headquarters, "KNTDS Guidebook," pp. 8-9, 2017.
  10. Gyujin Choi, and Younghwan Kim, "Development for Software Maintenance management tools," Proceedings of The 2018 Korea Software Congress, pp. 447-449, 2018.
  11. Ministy of National Defense, "National Defense Information System Project Management Directions," 2010.
  12. Kiwang Kim, and Dongsu Kang, "C4I Maintenance Priority Decision using fault analysis methods," Proceedings of The Korea Society of Computer and Information Conference, Vol. 25, No. 2, pp. 25-28, 2017.
  13. Eunjoo Jeong, and Cheonsoo Yoo, "A Software Maintenance Cost Estimation Model based on Real Maintenance Efforts," Journal of Information Technology Applications and Management, Vol. 19, No. 2, pp. 181-196, 2012. https://doi.org/10.21219/JITAM.2012.19.2.181
  14. Byoungchol Lee, and Sungyul Rhew, "The Maintenance Cost Estimation Model for Information System Maintenance Based on the Operation, Management and Service Metrics," Journal of The Korea Society of Computer and Information, Vol. 18, No. 5, pp. 77-85, 2013. DOI: 10.9708/jksci.2013.18.5.077
  15. ISO/IEC-14764, Information Technology-Software Maintenance
  16. Jihee Nam, and Dongsu Kang, "Analysis of ODT File Fuzzing Testcase in North Korea using Feature Selection Method," Proceedings of The Korea Information Processing Society Spring Conference 2019, Vol. 26, No. 1, pp. 324-327, 2019.
  17. M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and H. Witten, "The WEKA Data Mining Software: An Update," ACM SIGKDD Explorations newsletter, Vol. 11, No. 1, pp. 10-18, 2009. https://doi.org/10.1145/1656274.1656278
  18. E. Frank, M. Hall, G. Holmes, and H. Witten, "Data Mining in bioinformatics using WEKA," Bioinformatics Application Note, Vol. 20, No. 15, pp. 2479-2481, 2004. https://doi.org/10.1093/bioinformatics/bth261
  19. G. Holmes, A. Donkin, and H. Witten, "WEKA: a machine learning workbench," University of Waikato Computer Science Working Papers, 1994.
  20. R. Garner, "WEKA: The Waikato Environment for Knowledge Analysis," Proceedings of the New Zealand Computer Science Research Students Conference, 1995.
  21. Kiwang Kim, and Dongsu Kang, "C4I Maintenance Priority Decision using fault analysis methods," Proceedings of The Korea Society of Computer and Information Conference, Vol. 25, No. 2, pp. 25-28, 2017.