Zobrazeno 1 - 10
of 199
pro vyhledávání: '"Huang, Renke"'
Autor:
Yang, Shuo, Lin, Xingwei, Chen, Jiachi, Zhong, Qingyuan, Xiao, Lei, Huang, Renke, Wang, Yanlin, Zheng, Zibin
The rapid advancement of blockchain platforms has significantly accelerated the growth of decentralized applications (DApps). Similar to traditional applications, DApps integrate front-end descriptions that showcase their features to attract users, a
Externí odkaz:
http://arxiv.org/abs/2408.06037
Autor:
Evangelista, Francesco A., Li, Chenyang, Verma, Prakash, Hannon, Kevin P., Schriber, Jeffrey B., Zhang, Tianyuan, Cai, Chenxi, Wang, Shuhe, He, Nan, Stair, Nicholas H., Huang, Meng, Huang, Renke, Misiewicz, Jonathon P., Li, Shuhang, Marin, Kevin, Zhao, Zijun, Burns, Lori A.
Forte is an open-source library specialized in multireference electronic structure theories for molecular systems and the rapid prototyping of new methods. This paper gives an overview of the capabilities of Forte, its software architecture, and exam
Externí odkaz:
http://arxiv.org/abs/2405.10197
We present a reduced-cost implementation of the state-averaged driven similarity renormalization group (SA-DSRG) based on the frozen natural orbital (FNO) approach. The natural orbitals (NOs) are obtained by diagonalizing the one-body reduced density
Externí odkaz:
http://arxiv.org/abs/2312.07008
Autor:
Huang, Qiuhua, Huang, Renke, Yin, Tianzhixi, Datta, Sohom, Sun, Xueqing, Hou, Jason, Tan, Jie, Yu, Wenhao, Liu, Yuan, Li, Xinya, Palmer, Bruce, Li, Ang, Ke, Xinda, Vaiman, Marianna, Wang, Song, Chen, Yousu
This paper has delved into the pressing need for intelligent emergency control in large-scale power systems, which are experiencing significant transformations and are operating closer to their limits with more uncertainties. Learning-based control m
Externí odkaz:
http://arxiv.org/abs/2310.05021
Web3, the next generation of the Internet, represents a decentralized and democratized web. Although it has garnered significant public interest and found numerous real-world applications, there is a limited understanding of people's perceptions and
Externí odkaz:
http://arxiv.org/abs/2305.00427
Autor:
Hossain, Ramij R., Yin, Tianzhixi, Du, Yan, Huang, Renke, Tan, Jie, Yu, Wenhao, Liu, Yuan, Huang, Qiuhua
This article proposes a model-based deep reinforcement learning (DRL) method to design emergency control strategies for short-term voltage stability problems in power systems. Recent advances show promising results in model-free DRL-based methods for
Externí odkaz:
http://arxiv.org/abs/2212.02715
Autor:
Huang, Renke
The contributions of the research are (a) an infrastructure of data acquisition systems that provides the necessary information for an automated EMS system enabling autonomous distributed state estimation, model validation, simplified protection, and
Externí odkaz:
http://hdl.handle.net/1853/53518
In this work, we propose a quantum unitary downfolding formalism based on the driven similarity renormalization group (QDSRG) that may be combined with quantum algorithms for both noisy and fault-tolerant hardware. The QDSRG is a classical polynomial
Externí odkaz:
http://arxiv.org/abs/2208.08591
Autor:
Huang, Qiuhua, Huang, Renke, Yin, Tianzhixi, Datta, Sohom, Sun, Xueqing, Hou, Jason, Tan, Jie, Yu, Wenhao, Liu, Yuan, Li, Xinya, Palmer, Bruce, Li, Ang, Ke, Xinda, Vaiman, Marianna, Wang, Song, Chen, Yousu
Publikováno v:
In Electric Power Systems Research October 2024 235
Publikováno v:
In Applied Energy 1 January 2025 377 Part A