id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ajst-10387	Zhang, Congming; Yang, Zicheng; Gao, Shaofei	Short Term Wind Power Prediction Based on CEEMDAN-LSTM	2023	5	.pdf	application/pdf	2541	144	60	China Abstract: To improve the accuracy of wind power prediction, a wind power prediction method based on time series decomposition and error correction is proposed. Keywords: Wind power prediction, CEEMDAN, Deep Learning, LSTM; MIC.	cache/ajst-10387.pdf	txt/ajst-10387.txt