Short-Term Wind Power Forecasting: A Novel Enhanced Gate-Based Deep-Learning Model Containing a Metaheuristic Algorithm with an Intelligent Position Navigation Optimization Strategy

dc.contributor.author	Xu, Shun-Qing
dc.contributor.author	Tang, Yu
dc.date.accessioned	2026-08-20T11:18:06Z
dc.date.available	2026-08-20T11:18:06Z
dc.date.copyright	2025/09/13
dc.date.issued	2025
dc.identifier.other	JLEED9.EYENG-6163.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl1/handle/yetl/4311996
dc.description.abstract	AbstractWind energy generation technology has facilitated the diversification and transformation of energy sources, while also improving the sustainability and cleanliness of energy. However, the complex and variable external environment introduces ...
dc.publisher	American Society of Civil Engineers
dc.title	Short-Term Wind Power Forecasting: A Novel Enhanced Gate-Based Deep-Learning Model Containing a Metaheuristic Algorithm with an Intelligent Position Navigation Optimization Strategy
dc.type	Journal Article
dc.journal.volume	151
dc.journal.issue	6
dc.journal.title	Journal of Energy Engineering
dc.identifier.doi	10.1061/JLEED9.EYENG-6163
dc.journal.fristpage	04025070-1
dc.journal.lastpage	04025070-14
dc.page	14
dc.tree	Journal of Energy Engineering:;2025:;Volume ( 151 ):;issue: 006
dc.contenttype	Fulltext