Dynamic Multi-Swarm Differential Learning Quantum Bird Swarm Algorithm and Its Application in Random Forest Classification Model

Table 15

Performance of various well data.

Well	Classification model	RMSE	MAE	Accuracy (%)	Running time (s)
W1	RF	0.3326	0.1106	88.94	1.5167
	SVM	0.2681	0.0719	92.81	4.5861
	BSA-RF	0.3269	0.1069	89.31	1.8064
	DMSDL-BSA-RF	0.2806	0.0788	92.13	2.3728
	DMSDL-QBSA-RF	0.2449	0.0600	94.00	1.4663
W2	RF	0.4219	0.1780	82.20	3.1579
	SVM	0.2983	0.0890	91.10	4.2604
	BSA-RF	0.3963	0.1571	84.29	1.2979
	DMSDL-BSA-RF	0.2506	0.062827	93.72	1.6124
	DMSDL-QBSA-RF	0.2399	0.0576	94.24	1.2287
W3	RF	0.4028	0.1622	83.78	2.4971
	SVM	0.2507	0.0628	93.72	2.1027
	BSA-RF	0.3631	0.1318	86.81	1.3791
	DMSDL-BSA-RF	0.2341	0.0548	94.52	0.3125
	DMSDL-QBSA-RF	0.0519	0.0027	99.73	0.9513