id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
cana-6245	N. Sekar, S. Nithya	Deep Learning-Driven Smart Parking Reservation System for Urban Traffic Management	2025	30	.pdf	application/pdf	8441	437	49	Table 3: datasets characteristic Datasets Attribute min max Standard deviation (SD) P1 Real 0 152 58.5 P2 Real 0 132 29.0 P3 Real 0 151 42.2 Accuracy and Efficiency Comparison among parking models Both the TCN and LSTM networks achieved good accuracy on the real and synthetic datasets, as shown in Table 4. Valuing parking prediction models with errors The evaluation results of each model's accuracy in predicting vehicle parking locations are shown in Figure 8.	cache/cana-6245.pdf	txt/cana-6245.txt