id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ajset-592	Song, Yu-Jie; Ma, Jian-Guo	DEEP KOOPMAN NEURAL NETWORKS FOR NONLINEAR PROCESS MONITORING IN STOCHASTIC PRODUCTION SYSTEMS	2023	15	.pdf	application/pdf	6138	419	55	Over the past few decades, researchers have developed several methods for SPS process monitoring. The universal approximation theorem underscores the potential of neural networks to represent any function between inputs and outputs [15], making them an attractive option for SPS process monitoring.	cache/ajset-592.pdf	txt/ajset-592.txt
