Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Guobing Wu"'
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
Recently, the power systems with a high penetration of renewables and power electronics have come into being. In these power systems, complex system dynamics, emergency faults, and insufficient frequency regulation reserve pose threats to system freq
Externí odkaz:
https://doaj.org/article/12358f5589dc4be189422c31c6fc6628
Autor:
Yang Liu, Pingping Xie, Yinguo Yang, Qiuyu Lu, Xiyuan Ma, Changcheng Zhou, Guobing Wu, Xudong Hu
Publikováno v:
Frontiers in Energy Research, Vol 11 (2024)
In this work, modal decomposition is employed to generate more data for matching scenarios with more complex topography for predicting wind power output in the case of complex terrain. The existing literature shows that a single wind power output for
Externí odkaz:
https://doaj.org/article/4a345feec65a4510961057487b93222e
Publikováno v:
Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022).
Publikováno v:
Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022).
Publikováno v:
China Finance Review International, 2015, Vol. 5, Issue 4, pp. 402-420.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/CFRI-11-2014-0097
Autor:
Yue Zhao, Guobing Wu, Qiuna Cai, Long Wang, Jue Yu, Hui Song, Yujun Sun, Zelin Wang, Xiaojuan Dai
Publikováno v:
2022 2nd International Conference on Electrical Engineering and Control Science (IC2ECS).
Publikováno v:
Advances in Energy, Environment and Chemical Engineering Volume 1 ISBN: 9781003330165
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::89269b46f6653c7abdcf880567e2fa80
https://doi.org/10.1201/9781003330165-35
https://doi.org/10.1201/9781003330165-35
Publikováno v:
2022 Asian Conference on Frontiers of Power and Energy (ACFPE).
Publikováno v:
Annals of Translational Medicine. 10:1349-1349
Publikováno v:
Multimedia Tools and Applications. 72:1257-1283
In this paper, we propose novel hybrid approaches to annotate videos in valence and arousal spaces by using users' electroencephalogram (EEG) signals and video content. Firstly, several audio and visual features are extracted from video clips and fiv