연구동향 분석

데이터 마이닝 기법을 이용한 국내 항공기 제조기업의 경쟁력 평가에 관한 연구 = A Study on the Competitiveness Evaluation of the Domestic Aircraft Manufacturing Enterprises Using Data Mining Techniques

옥주선 2022년

    • more
논문상세정보
인용/피인용
' 데이터 마이닝 기법을 이용한 국내 항공기 제조기업의 경쟁력 평가에 관한 연구 = A Study on the Competitiveness Evaluation of the Domestic Aircraft Manufacturing Enterprises Using Data Mining Techniques' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • Aircraft Manufacturing Enterprises(항공기 제조기업)
  • Competitiveness(경쟁력)
  • Data Mining(데이터 마이닝)
  • Feature Extraction(특징 추출)
  • Principal Component Analysis (주성분분석)
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
15 0

0.0%

' 데이터 마이닝 기법을 이용한 국내 항공기 제조기업의 경쟁력 평가에 관한 연구 = A Study on the Competitiveness Evaluation of the Domestic Aircraft Manufacturing Enterprises Using Data Mining Techniques' 의 참고문헌

  • Evaluation of Supplier Performan ce in Commercial Aircraft Manufacturing Industry
    Jong Sae Kim and Jae Bum Hong Vol . 32 , No . 8 : 1425-1444 [2019]
  • Evaluation of C ore Competitiveness of Aerospace Enterprise Based on Dual Competence Per spective
  • Design for the competitiveness index system of aviation & aerospace manufacture industry on basis of GEM-Pearson-VC combination method
  • Aviation Industry Outlook and Countermeasures
  • A Study to Enhance International Competitiveness of the Korean Aircraft Industry
    Ha-Gyo Jung and Ju Hyung Lee vol.26 ( 2 ) : 205-237 [2010]
  • A Study on the Technologic al Competitiveness of Aircraft Infra Industries by using Patents
    Ha-Gyo Jung and Kyu-Seong Whang Vol.25 ( 2 ) : 43 ? 57 [2011]
  • 9. Chursin A. and Makarov Yu, 2015, Management of Competitiveness, Sprin ger International Publishing AG. Switzerland : 193-199, 249-250
    [2015]
  • 7. Jin-ki Hong and Jun Hwan Choi, 2014, Plans for The Development of Th e Aircraft Industry in Gyeongnam Region Through Competitiveness Analysis, BOK Gyeongnam Regional Economic Review : 13-42
    [2014]
  • 4. Hyeong-Bok No, 2010, A Study on Ways to Strengthen the Competitiven ess of the Aircraft Industry, Korea Aerospace Industry Association, Aerospa ce Industry Seal No. 107 : 12-15
  • 3. Wikipedia, Data Mining, https://en.wikipedia.org/wiki/Data_mining
  • 22. Gyeongnam Technopark Aerospace Center, 2021, Export revitalization pl an for Gyeongnam Airospace SME’s
  • 21. Counterpoint, Global mark share analysis of aerostructure and engine par ts, 2021 Aerostructure, https://www.counterpointresearch.com/
  • 20. Gyeongnam Technopark Aerospace Center, Member company status, http s://www.kav.or.kr/eng/main/main.php
  • 2. Ministry of Trade, Industry and Energy, 2021, The 3rd Aerospace Indust ry Development Master Plan (‘21~’30), Ministry of Trade, Industry and Ene rgy notice No. 2021-179 : 16–17
  • 19. Scikit-learn, Linear Models, https://scikit-learn.org/stable/modules/linear _model.html
  • 18. Korea Aerospace Industry Association, 2021, Status of major global aero space companies (2020), Aerospace Industry Staistics : 70 – 72
    [2020]
  • 17. Cook’s Distance / Cook’s D: Definition, Interpretation, https://www.statist icshowto.com/cooks-distance/
  • 16. Statsmodels, https://www.statsmodels.org/stable/index.html
  • 15. Dodomira, All about data preprocessing, http://www.dodomira.com/2016/1 0/20/how_to_eda/
  • 14. Tistory, Data Mining, https://iamdaisy.tistory.com/19
  • 13. Charu C. Aggarwal. 2015, Data Mining The Text Book, Springer Internat ional Publishing AG, Switzerland : 1 – 75.
    [2015]
  • 12. Rolandberger, Three ways to maintain competitiveness based on leverage value chain restructuring, https://www.rolandberger.com/en/Insights/Publicatio ns/How-the-Covid-19-crisis-is-expected-to-impact-the-aerospace-indu stry.html