id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ajst-26910	Ji, Feifan	Time Series Prediction Method for Meteorological Data Based on the ARIMA-LSTM Model	2024	4	.pdf	application/pdf	2602	131	42	By combining the ability of ARIMA model in capturing linear relationship and short-term fluctuation, and the strong ability of LSTM network in dealing with nonlinear problems and long-term dependence, a hybrid forecasting model is constructed in this article, which can not only accurately reflect the linear characteristics of meteorological data time series, but also effectively capture its nonlinear changes. Canada Abstract: The purpose of this article is to explore and verify the effectiveness and advantages of ARIMA-LSTM hybrid model in meteorological data time series prediction.	cache/ajst-26910.pdf	txt/ajst-26910.txt