id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fcis-22628	Wang, Ning; Hou, Xiaojun; Ma, Jikun; Yuan, Bingbing; Xin, Fuyan	Research on Big Data Intelligent System for Fault Diagnosis of Computer Aided Ship Power System	2024	5	.pdf	application/pdf	3981	177	39	In the stage of building fault diagnosis model, the research team carefully selected representative fault sample 68 data based on actual fault cases for training and verifying the intelligent fault diagnosis model that integrates machine learning and deep learning algorithms. Secondly, in view of the nonlinear and time-varying characteristics of ship power system faults, this study designs and implements a fault diagnosis model that integrates intelligent algorithms such as machine learning and deep learning.	cache/fcis-22628.pdf	txt/fcis-22628.txt