Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Liquid Metal Nanotransformers for Drug-Resistant Pan-Cancer Therapy in Patient-Derived Organoids.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Comparison of efficacy between medial double-incision approach and medial-lateral double-incision approach in endoscopic surgery for refractory plantar fasciitis complicated with calcaneal spur.

The Journal of foot and ankle surgery : official publication of the American College of Foot and Ankle Surgeons·2026
Same author

Alterations in neurovascular coupling are present in adolescent patients with major depressive disorder: An integrated resting-state fMRI and arterial spin labeling study.

Journal of affective disorders·2026
Same author

Liquid Metal Microsphere-Embedded Conductive Hydrogel Enables Electro-Responsive Drug Release for Wound Healing.

ACS applied materials & interfaces·2025
Same author

Mechanical properties and acoustic emission activity characteristics of different coal-rock ratios under uniaxial cyclic loading.

Scientific reports·2025
Same author

Bioinspired wood-based wedge-shaped surface with gradient wettability for enhanced directional liquid transport and fog harvesting.

Materials horizons·2025

相关实验视频

Updated: Jun 21, 2025

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
06:09

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation

Published on: September 8, 2023

557

基于CEEMDAN和TCN-LSTM的负载预测方法

Luo Heng1,2, Cheng Hao1, Liu Chen Nan1

  • 1School of Electronics and Information Engineering, University of Science and Technology of Suzhou, Suzhou, Jiangsu, China.

PloS one
|July 5, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了使用完全集成的实证模态分解 (CEEMDAN) 和时间卷积网络-长期短期存储器 (TCN-LSTM) 网络的改进的功率负载预测方法. 这种新的方法提高了对波动功率负载的预测准确性和稳定性.

更多相关视频

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

42.6K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.7K

相关实验视频

Last Updated: Jun 21, 2025

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
06:09

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation

Published on: September 8, 2023

557
Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

42.6K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.7K

科学领域:

  • 电气工程 电气工程
  • 数据科学数据科学数据科学
  • 应用数学 应用数学 应用数学

背景情况:

  • 由于高的随机性和波动性,功率负载预测面临着挑战.
  • 准确的预测对于高效的电网管理和稳定性至关重要.

研究的目的:

  • 提出一种新的功率负载预测方法,解决准确性和稳定性问题.
  • 利用先进的信号分解和深度学习来改善预测.

主要方法:

  • 使用完全集成的实证模态分解 (CEEMDAN) 来将原始负载数据分解为稳定的子序列.
  • 采用样本来进行后续重组.
  • 应用一个时间卷积网络-长期短期记忆 (TCN-LSTM) 模型用于特征提取和预测.

主要成果:

  • 与传统预测技术相比,CEEMDAN-TCN-LSTM方法的准确性更高.
  • 拟议的模型在负载预测任务中显示出优异的预测效应.
  • 验证使用来自澳大利亚新南威尔士州的电力合规数据进行.

结论:

  • CEEMDAN-TCN-LSTM方法在功率负载预测准确性和稳定性方面提供了显著的改进.
  • 这种方法为未来的电力负载预测研究和应用提供了宝贵的参考.