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NTIS 바로가기한국산학기술학회논문지 = Journal of the Korea Academia-Industrial cooperation Society, v.22 no.3, 2021년, pp.234 - 241
박천규 (공군 제2방공유도탄여단) , 마정목 (국방대학교 국방과학학과)
By recognizing the importance of demand forecasting, the military is conducting many studies to improve the prediction accuracy for repair parts. Demand forecasting for repair parts is becoming a very important factor in budgeting and equipment availability. On the other hand, the demand for intermi...
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Defense Agency for Technology and Quality(DTaQ), Defense Science and Technology Glossary[Internet], DTaQ, c2017 [cited 2017], Available From: http://dtims.dtaq.re.kr:8070/search/detail/term.do?tmnl_idT0007321 (accessed Oct. 25 2020)
Y. J. Lee, Ministry of Defense "Reduce 12.9 billion won by increasing the accuracy of demand forecasting" [Internet], Yunhapnews, c2017 [cited 2017 Nov. 24], Available From: https://www.yna.co.kr/view/AKR20171124043200014?input1195m (accessed Oct. 25, 2020)
S. H. Kang, Patriot battery shuts down for 132 days[Internet], Newsis, c2013 [cited 2013 Oct. 14], Available From: https://newsis.com/ar_detail/view.html?ar_idNISX20131014_0012431822&cID10301&pID10300 (accessed Oct. 25, 2020)
Airforce Headquarters, Maintenance of Repair parts, p.69, Airforce Headquarters, 2019, pp.12.
Airforce Logistics Command, '17 Research Results of Demand Forecasting Improvement Techniques, p.25, Airforce Logistics Command, 2017, pp.12.
H. T. Kim, S. H. Kim, "Data mining based army repair parts demand forecast", Journal of the Korean Data & Information Science Society, Vol.30, No.2, pp.429-444, March 2019. DOI: https://doi.org/10.7465/jkdi.2019.30.2.429
J. S. Kim, J. S. Hwang, J. W. Jung "A New LSTM Method Using Data Decomposition of Time Series for Forecasting the Demand of Aircraft Spare Parts", Korean Management Science Review, Vol.37, No.2, pp.1-18, June 2020. DOI: https://doi.org/10.7737/KMSR.2020.37.2.001
J. D. Croston, "Forecasting and Stock Control for Intermittent Demands", Operational Research Quarterly, Vol.23, pp.289-303, September 1972. DOI: https://doi.org/10.1057/jors.1972.50
D. W. Choi, A Data Mining Approach for Forecasting the Demand of Accidental Automobile Spare Parts with External Factors, Master's thesis, Yonsei University of Information Industrial Engineering, Seoul, Korea, pp.5-8, 2013.
B. H. Oh, A study on weapon system spare parts intermittent demand forecasting using deep learning, Master's thesis, Korea University of Information and Communication, Seoul, Korea, pp.2-10, 2017.
T. G. Kim, J. M. Ma "A Data Mining Approach for Intermittent Demand Forecasting of Aircraft Spare Parts - Focusing on the E-737(AEW&C: Airborne Early Warning & Control) Spare Parts -", Journal of the AMSOK, Vol.16, No.4, pp.155-164, August 2018. DOI: https://doi.org/10.30529/amsok.2018.16.4.008
A. Ghobbar, C. Friend, "Evaluation of forecasting methods for intermittent parts demand in the field of aviation: a predictive model", Computer and Operation Research, Vol.30, No.1, pp.2097-2114, December 2003. DOI: https://doi.org/10.1016/S0305-0548(02)00125-9
Airforce Air Defence Missile Command, '15 Operational equipment defect analysis and management measures, p.19, Airforce Air Defence Missile Command, 2015, pp.10-14.
Galit Shmueli, Nitin R. Patel, Peter C. Bruce, Data Mining for Business Intelligence, p.455, E&B PLUS, 2012, pp.23-24, 265-272.
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