id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fcis-23828	Lyu, Guangqiang; Xie, Yanjing	Research on Optimization Method of Dredging Robot based on Deep Learning	2024	3	.pdf	application/pdf	1975	86	46	Deep learning and PID controller trajectory comparison After further analysis of the error situation found that after 1000 training of deep reinforcement learning model can track error stability control within 0.02m, and the maximum error of the PID controller is close to 0.04m, and the error fluctuation is more obvious, shows the deep reinforcement learning in the advantage of track tracking, and provide valuable reference for research and application in related fields. Deep learning models can learn and improve trajectory planning strategies based on historical data and real-time feedback	cache/fcis-23828.pdf	txt/fcis-23828.txt