군 운용환경을 고려한 상용차량 불용여부 판단 모델 연구
A study on Decision Model of Disuse Status for the Commercial Vehicles Considering the Military Operating Environment
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초록
현재 군에서 운용하는 차량 중에 민간에서 사용하고 있는 상용차량이 차지하는 비중이 58%로 매우높고 앞으로 더욱 증가할 계획이다. 군에서 상용차량의 비중이 높아진 만큼 상용차량의 불용처리 결정여부도 중요한 문제 중의 하나이다. 현재 상용차량의 불용처리 결정은 차량 기술검사관이 설계수명과차량사용 정보를 이용해서 주관적으로 판단하고 있으나, 군 운용환경에 따른 차이가 반영되어 있지않고 객관적인 판단 기준이 제시되어 있지는 않다. 본 연구는 군 운용환경을 고려하여 상용차량의불용여부를 판단하는 모델을 개발하는 것이다. 연구에서 활용한 자료는 육·해·공군의 승용차, 승합차량, 트럭 세 가지 상용차량 1,746대였고, 운용지역, 기후특성, 차량상태 등의 정보를 이용하여 분류 머신러닝기법을 이용해 불용여부 판단 모델을 구축하였다. 제안하는 불용여부 판단 모델은 정확도가 평균적으로약 97%였으며, 야전에서도 사용할 수 있는 형태의 모델이다. 연구결과를 바탕으로 향후 상용차량 불용여부 판단 모델 성능 향상 방안과 군수정보체계 내에 새롭게 구축해야 할 데이터 구축 방향을 장·단기적으로 정책 제언하였다.
Abstract
The proportion of commercial vehicles currently used by the private sector among the vehicles operated by the military is very high at 58% and plans to increase further in the future. As the proportion of commercial vehicles in the military has increased, it is also an important issue to determine whether to disuse of commercial vehicles. At present, the decision of disuse of commercial vehicles is subjectively judged by vehicle technical inspector using design life and vehicle usage information. However, the difference according to the military operation environment is not reflected and objective judgment criteria are not presented. The purpose of this study is to develop a model to determine the disuse status of commercial vehicles in consideration of military operating environment. The data used in the study were 1,746 commercial vehicles of three types: cars, vans and trucks. Using the information of the operating area, climate characteristic, vehicle condition the decision model of disuse status was constructed using the classification machine learning technique. The proposed decision model of disuse status has an average accuracy of about 97% and can be used in the field. Based on the results of the study, the policy suggestions were proposed in the short and long term to improve the performance of decision model of disuse status of commercial vehicles in the future and to establish a new data construction method within the logistics information system.
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