Bayesian Inference of Ammunition Consumption Based on Normal-Inverse Gamma Distribution. (14th April 2022)

• Record Type: Journal Article
• Authors: Liu, Haobang; Shi, Xianming; Chen, Xiaojuan; Li, Yuan; Zhao, Mei; Jiang, Yongchao
• Other Names: Shen Mouquan Academic Editor.
• Is Part Of: Discrete dynamics in nature and society. Volume 2022(2022)
• Publication Date: 2022-04-14
• Subjects: System analysis -- Periodicals; Dynamics -- Periodicals; Chaotic behavior in systems -- Periodicals; Differentiable dynamical systems -- Periodicals; 003.05
• DOI: 10.1155/2022/6365712
• Languages: English
• ISSNs: 1026-0226

Abstract

Abstract : To address the problems of high cost of new ammunition experiment, few data of field test and low accuracy of consumption prediction, this article proposes a Bayesian estimation method of ammunition consumption based on normal-inverse gamma distribution, and estimates the hyperparameters in the prior distribution through the prior information from the consumption of ammunition under different damage degrees of point targets, based on the normal distribution phenomenon of ammunition consumption at each damage degree. It is to establish a Bayesian estimation model for ammunition consumption under different damage degrees according to field test data based on Bayesian formula and solve for its posterior distribution. The example proves that the estimation results of ammunition consumption for point target with different damage degrees based on this method is more scientific and reasonable according to various prior information.