Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Analysis of scientific military training data using zero-inflated and Hurdle regression

영과잉 및 허들 회귀모형을 이용한 과학화 전투훈련 자료 분석

  • Kim, Jaeoh (Department of Statistics, Korea University) ;
  • Bang, Sungwan (Department of Mathematics, Korea Military Academy) ;
  • Kwon, Ojeong (Department of Industrial and Systems Engineering, KAIST)
  • 김재오 (고려대학교 통계학과) ;
  • 방성완 (육군사관학교 수학과) ;
  • 권오정 (한국과학기술원 산업 및 시스템공학과)
  • Received : 2017.09.11
  • Accepted : 2017.11.02
  • Published : 2017.11.30
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Abstract

The purpose of this study is to analyze military combat training data to improve military operation and training methods and verify required military doctrine. We set the number of combat disabled enemies, which the individual combatants make using their weapons, as the response variable regarding offensive operations from scientific military training data of reinforced infantry battalion. Our response variable has more zero observations than would be allowed for by the traditional GLM such as Poisson regression. We used the zero-inflated regression and the hurdle regression for data analysis considering the over-dispersion and excessive zero observation problems. Our result can be utilized as an appropriate reference in order to verify a military doctrine for small units and analysis of various operational and tactical factors.

본 연구는 과학과 전투훈련 자료를 분석하여 작전 및 군사훈련 방법을 향상하고 필요한 군사교리를 검증하기 위한 것이다. 우리는 과학화 전투훈련 중 대대급 공격작전에 대해 개별 전투원이 공격작전간 개인 화기를 이용하여 적을 중상 이상의 전투불능 상태로 만든 인원수를 반응변수로 둔다. 본 연구의 반응변수는 영이 지나치게 많이 관측되어 전통적인 일반화 선형모형에서 분석이 제한된다. 우리는 과대산포 및 영이 과도하게 관측된 점을 고려하여 영과잉 회귀모형과 허들 회귀모형을 자료에 적합하여 분석한다. 우리의 분석 결과는 대한민국 육군의 보병대대와 같은 소부대의 다양한 작전 및 전술적 요인에 대한 분석과 전술제대의 군사교리 검증함에 있어 적절한 참고자료로 활용될 수 있다.

Keywords

Acknowledgement

Supported by : 한국연구재단

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