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LSTM and Bayesian Computation in Uncertainty Quantification for Wind Energy Forecasting

Title:	LSTM and Bayesian Computation in Uncertainty Quantification for Wind Energy Forecasting
Authors:	Al-Mahmodi, Mohammed^Aff16; Mansi, Hanan^Aff16; Cheng, Changqing^Aff16; Heliodore, Frederic^Aff17; Wang, Yong^Aff16
Contributors:	Chaari, Fakher, Series Editor^Aff1; Gherardini, Francesco, Series Editor^Aff2; Ivanov, Vitalii, Series Editor^Aff3; Haddar, Mohamed, Series Editor^Aff4; Cavas-Martínez, Francisco, Editorial Board Member^Aff5; di Mare, Francesca, Editorial Board Member^Aff6; Kwon, Young W., Editorial Board Member^Aff7; Tolio, Tullio A. M., Editorial Board Member^Aff8; Trojanowska, Justyna, Editorial Board Member^Aff9; Schmitt, Robert, Editorial Board Member^Aff10; Xu, Jinyang, Editorial Board Member^Aff11; Srihari, Krishnaswami, editor^Aff12; Khasawneh, Mohammad T., editor^Aff13; Yoon, Sangwon, editor^Aff14; Won, Daehan, editor^Aff15
Source:	Flexible Automation and Intelligent Manufacturing: The Future of Automation and Manufacturing: Intelligence, Agility, and Sustainability : Proceedings of FAIM 2025, June 21–24, 2025, New York City, NY, USA, Volume 1. :407-415
Database:	Springer Nature eBooks