id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
easat-10722	Dehghanian, Seyed Ahmadreza; Heidary, Sahand; Shams, Danial; Pour, Ali Mastali; Zahedi, Rahim	Deep learning for solar power forecasting: A robust stacked LSTM algorithm for operational applications	2025	10	.pdf	application/pdf	4377	236	41	Published: 27 October 2025 * Correspondence: rahimzahedi@ut.ac.ir Deep learning for solar power forecasting: A robust stacked LSTM algorithm for operational applications Seyed Ahmadreza Dehghanian1*, Sahand Heidary2, Danial Shams3, Ali Mastali Pour4, Rahim Zahedi5 1Department of Computer Engineering, Yazd University, Yazd, Iran — Master’s Student in Software Engineering, Iran; ahmadrzdeh@gmail.com (S.A.D.). [1] J. Zhang, Metrics for evaluating the accuracy of solar power forecasting, in Proceedings of the 2013 International Workshop on the Integration of Solar Power into Power Systems (pp.	cache/easat-10722.pdf	txt/easat-10722.txt