The application of Bayesian network in battle damage assessment
Chenhan Li, Jian Xin Huang · 2014
With the ability of data mining and reasoning, Bayesian network could well solve the problems with uncertainties and incompletion, and the result of assessment is closer to the real condition. Therefore, the Bayesian network is to solve the problems in battle damage assessment. The paper firstly analyses the damage indexes and variables of UAV-to-ground attacking. Given conditional probability by vague arithmetic and experts' experience, the paper builds the model of Bayesian network. At last, the paper applies network reasoning to battle damage assessment and proves the validity of Bayesian by experiments.