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

Table 7

Parameters of node Ai learned by 100 samples.

	3000-MLE	100-MLE	100-MCE
T	Ai(1, 2)	Ai(1, 2)	Ai(1, 2)
T1 (strong)	(0.9024, 0.0976)	(0.9500, 0.0500)	(0.9333, 0.0667)
T2 (middle)	(0.5520, 0.4480)	(0, 5641, 0.4359)	(0.5731, 0.4269)
T3 (middle)	(0.2604, 0.7396)	(0.2683, 0.7317)	(0.2725, 0.7275)