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Theoretical Methods and Application Prospects for Uncertainty Quantification in Distribution Network Operation Under the Influence of Stochastic Source-load Journal article
Han, Wang, Xiaoyuan, Xu, Zheng, Yan, Hongxun, Hui, Xiaotao, Fang. Theoretical Methods and Application Prospects for Uncertainty Quantification in Distribution Network Operation Under the Influence of Stochastic Source-load[J]. Journal of Global Energy Interconnection, 2022, 5(3), 230-241.
Authors:  Han, Wang;  Xiaoyuan, Xu;  Zheng, Yan;  Hongxun, Hui;  Xiaotao, Fang
Favorite | TC[Scopus]:1 | Submit date：2024/01/25
Distribution Network  Global Sensitivity Analysis  Multi-fidelity Model  Stochastic Source-load  Uncertainty Quantification  
Distribution-aware hierarchical weighting method for deep metric learning Conference paper
Zhu, Yinong, Feng, Yong, Zhou, Mingliang, Qiang, Baohua, Leong Hou, U., Zhu, Jiajie. Distribution-aware hierarchical weighting method for deep metric learning[C], NEW YORK, NY 10017 USA:IEEE, 2021, 1770-1774.
Authors:  Zhu, Yinong;  Feng, Yong;  Zhou, Mingliang;  Qiang, Baohua;  Leong Hou, U.; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2022/05/13
Metric Learning  Distribution Quantification  Hierarchical Weighting  Relationship Maintenance  
Relationship-Aware Hard Negative Generation in Deep Metric Learning Conference paper
Huang, Jiaqi, Feng, Yong, Zhou, Mingliang, Qiang, Baohua. Relationship-Aware Hard Negative Generation in Deep Metric Learning[C], 2020, 388-400.
Authors:  Huang, Jiaqi;  Feng, Yong;  Zhou, Mingliang;  Qiang, Baohua
Favorite | TC[WOS]:1 TC[Scopus]:1 | Submit date：2023/04/19
Deep Metric Learning  Distribution Quantification  Minimum Spanning Tree  Relationship Preserving  Sample Generation