[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.9708/jksci.2020.25.01.141

A study on Decision Model of Disuse Status for the Commercial Vehicles Considering the Military Operating Environment

Lee, Jae-Ha (Dept. of Korea National Defense and Science, Korea National Defense University)
Moon, Ho-Seok (Dept. of Korea National Defense and Science, Korea National Defense University)

Publication Information

Journal of the Korea Society of Computer and Information / v.25, no.1, 2020 , pp. 141-149 More about this Journal

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.

Keywords

Disuse status; design life; service life; mileage; machine learning;

Citations & Related Records

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