相关实验视频

Updated: May 12, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

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嵌入了数据转换和多目标特征选择算法的增强框架,用于预测风力发电

Yahya Z Alharthi1, Haruna Chiroma2, Lubna A Gabralla3

  • 1Department of Electrical Engineering, College of Engineering, University of Hafr Albatin, 39524, Hafr Al Batin, Saudi Arabia. yalharthi@uhb.edu.sa.

Scientific reports
|May 9, 2025
PubMed
概括

准确的风能预测对于管理可再生能源至关重要. 这项研究引入了使用特征选择和混合深度循环网络长期短期存储模型的新框架,以显著提高风力发电预测的准确性.

关键词:
数据转换 - 数据转换.深度循环神经网络深度循环神经网络功能选择 功能选择长期的短期记忆 长期的短期记忆可再生能源是可再生的能源.风力轮机发电的动力是风力轮机的动力.

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