Table 9 Comparative analysis with prior studies.

Reference	Models	Key features	R²
⁶⁵	Ensemble		0.83
	RF		0.81
	Multi-layer perceptron ANN		0.76
	SVR		0.47
	Gaussian process regression		0.47
	Linear regression		0.46
	Gradient boosting		0.81
	K-nearest neighbors		0.68
²⁷		SHAP
	Ensemble		0.95
	Multi-layer perceptron		0.46
	XGBoost		0.78
	Gradient Boosting		0.80
	RF		0.80
	DT		0.76
	SVR		0.71
	Linear regression		0.36
⁶⁶	CG-BP ANN		0.91
Present study		SHAP and PDP
		Python GUI for immediate predictions
	SVR-GWO		0.96
	SVR-GTO		0.95
	ANN-GWO		0.92
	ANN-GTO		0.90

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