id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fcis-10208	Lu, Hongwei	LSTM-Based Stock Price Prediction	2023	4	.pdf	application/pdf	2299	155	62	In view of the high noise, nonlinearity and non-stationarity of stock price data, which makes it very difficult to accurately predict the stock price, this paper intends to use the long-short-term memory network (Long Short-Term Memory, LSTM) In the end, the optimization of the model based on the method of deep learning, and the attempt to improve the prediction accuracy of the model by fusing stock data from different sources are elaborated in detail.	cache/fcis-10208.pdf	txt/fcis-10208.txt