Table 10 Comparison between the proposed prediction approach and previous works.

Source	Prediction	Model	Features	Results				Year
First Proposed Prediction Approach	Initial SoC Required SoC	FDNN	Distance, Road Characteristics, and Weather Data	Index	SoC-In		SoC-Req	2025
				SMAPE	0.0007		0.00015
				MAE	0.00015		0.00013
				MSE	6.8*10⁻⁷		1.8*10⁻⁷
				RMSE	0.00083		0.00043
				R²	1		1
Second Proposed Prediction Approach	Initial SOC Required SOC Arrival Time Departure Time	FDNN	Distance, Road Characteristics, and Weather Data	Index	SoC-In		SoC-Req	2025
				SMAPE	0.00044		0.00018
				MAE	0.00017		0.00015
				MSE	5*10⁻⁷		4.2*10⁻⁷
				RMSE	0.00071		0.00065
				R²	1		1
Ref.³¹	SoC	ANN SVM Linear GPR Ensemble Boosting Ensemble Bagging	Battery Capacity Battery Voltage Battery Current and Battery Temperature	MSE	0.00054			2021
				MAE	0.00027
				RMSE	0.02329
				R²	0.999
Ref.³²	SL, Energy Consumption	RF, SVM, XGBoost, & ANN	HCD, Weather, Traffic, Events Data	SMAPE	9.92%			2021
				MAE	66.5 min
				SMAPE	11.6% Consumption
				R²	0.7
Ref.³³	Departure Time	XGBoost	HCD, Vehicle Type, Charging Location	MAE	82 min			2020
Ref.³⁴	Energy Requirements	XGBoost	HCD	MAE		4.6 kWh		2020
Ref.³⁴	Energy Requirements	XGBoost	HCD	R²		0.52		2020
Ref.³⁵	SL, Energy Consumption	Ensemble Model of SVM, RF, & DKDE	HCD	SMAPE		10.4% Duration		2019
Ref.³⁵	SL, Energy Consumption	Ensemble Model of SVM, RF, & DKDE	HCD	SMAPE		7.5% Consumption		2019

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