A Threat Assessment Method for Unmanned Aerial Vehicle Based on Bayesian Networks under the Condition of Small Data Sets

Table 6

Parameters of node Ac learned by 100 samples.

	3000-MLE	100-MLE	100-MCE
T	Ac(1, 2, 3)	Ac(1, 2, 3)	Ac(1, 2, 3)
T1 (strong)	(0.8102, 0.1399, 0.0499)	(0.7500, 0.2500, 0)	(0.7921, 0.1308, 0.0771)
T2 (middle)	(0.3027, 0.4038, 0.2935)	(0.1795, 0.3846, 0.4359)	(0.2627, 0.4122, 0.3252)
T3 (weak)	(0.2482, 0.3411, 0.4107)	(0.2927, 0.1707, 0.5366)	(0.2398, 0.3322, 0.4279)