Journal of Systems Engineering and Electronics ›› 2020, Vol. 31 ›› Issue (3): 567-577.doi: 10.23919/JSEE.2020.000035

• Systems Engineering • Previous Articles     Next Articles

Bayesian inference for ammunition demand based on Gompertz distribution

Rudong ZHAO1,2(), Xianming SHI1,*(), Qian WANG3(), Xiaobo SU1,4(), Xing SONG5()   

  1. 1 Department of Equipment Command and Management, Shijiazhuang Campus, Army Engineering University, Shijiazhuang 050003, China
    2 Unit 73127 of the PLA, Fuzhou 350503, China
    3 The Ninth Comprehensive Training Base of Army, Zhangjiakou 075000, China
    4 Army Infantry College of the PLA, Shijiazhuang 050003, China
    5 Unit 68303 of the PLA, Golmud 816000, China
  • Received:2019-06-18 Online:2020-06-30 Published:2020-06-30
  • Contact: Xianming SHI E-mail:zrd13376475476@126.com;x.m.shi@126.com;18003131595@163.com;giantsu030700@sina.com;flying506@163.com
  • About author:ZHAO Rudong was born in 1995. He received his Bachelor's degree in management from Changchun Institute of Technology in 2017 and Master's degree in management from the Army Engineering University in 2019. His research interests are ammunition support and equipment management. E-mail: zrd13376475476@126.com|SHI Xianming was born in 1975. He received his B.E. degree from the Academy of Ordnance Engineering in 1996, M.E. degree from the National University of Science and Technology in 2002, and Ph.D. degree from National University of Science and Technology in 2006. He is currently an associate professor in Shijiazhuang Campus of Army Engineering University. His research interests are equipment support and systems engineering. E-mail: x.m.shi@126.com|WANG Qian born in 1989. He received his B.E. degree from the University of Defense Science and Technology in 2011 and M.S. degree in military science from the Army University of Engineering in 2019. He is a lecturer in the Ninth Comprehensive Training Base of Army. His research interest is equipment support. E-mail: 18003131595@163.com|SU Xiaobo was born in 1978. He received his B.E. degree from the Armored Corps College of Engineering in 2001, and M.S. degree in military science from the Academy of Ordnance Engineering in 2009. He is pursuing his Ph.D. degree at the Army Engineering University. He is a lecturer in the Army Infantry College of the PLA. His research interest is equipment support. E-mail: giantsu030700@sina.com|SONG Xing was born in 1991. He received his B.E. degree from the Academy of Ordnance Engineering in 2013, and M.S. degree in military science from the Army University of Engineering in 2019. His research interest is equipment management. E-mail: flying506@163.com
  • Supported by:
    the Army Scientific Research(KYSZJWJK1744);the Army Scientific Research(012016012600B11403);This work was supported by the Army Scientific Research (KYSZJWJK1744; 012016012600B11403)

Abstract:

Aiming at the problem that the consumption data of new ammunition is less and the demand is difficult to predict, combined with the law of ammunition consumption under different damage grades, a Bayesian inference method for ammunition demand based on Gompertz distribution is proposed. The Bayesian inference model based on Gompertz distribution is constructed, and the system contribution degree is introduced to determine the weight of the multi-source information. In the case where the prior distribution is known and the distribution of the field data is unknown, the consistency test is performed on the prior information, and the consistency test problem is transformed into the goodness of the fit test problem. Then the Bayesian inference is solved by the Markov chain-Monte Carlo (MCMC) method, and the ammunition demand under different damage grades is gained. The example verifies the accuracy of this method and solves the problem of ammunition demand prediction in the case of insufficient samples.

Key words: ammunition demand prediction, Bayesian inference, Gompertz distribution, system contribution, Markov chain-Monte Carlo (MCMC) method