Table 10. Comparison of Different Machine Learning Methods with the F1-Score.

	Marco F1-score
method	LT (%) (<150 °C)	LT (%) (150–300 °C)	PD (%)	AD (%)	average (%)
MMFO-PNN	98.04	100.00	100.00	96.55	98.65
Sa-PNN	96.15	93.33	100.00	96.55	96.51
GWO-hybrid KELM	97.96	100.00	93.33	93.75	96.26
SaE-ELM	93.62	100.00	94.12	94.44	95.54
GA-PNN	95.83	94.12	100.00	89.66	94.90
MCS-BP	95.83	100.00	90.00	93.75	94.90
BA-PNN	96.15	100.00	92.31	89.66	94.53
MBA-BP	96.15	93.33	93.33	93.75	94.14
GA-SVM	94.34	93.33	90.91	96.55	93.78
PSO-PNN	96.15	82.35	100.00	88.89	91.85
PNN	89.29	76.92	100.00	88.89	88.77