Zobrazeno 1 - 10
of 286
pro vyhledávání: '"LIU Bingqi"'
Publikováno v:
He jishu, Vol 46, Iss 7, Pp 070502-070502 (2023)
BackgroundTraditional X-ray fluorescence spectrum analysis has the limitations of poor accuracy of the characteristic peak counting rate and shadow peak.PurposeThis study aims to propose a long and short term memory (LSTM) neural network model based
Externí odkaz:
https://doaj.org/article/72a401692794427690457c07a4155749
Autor:
Liu Bingqi, Hu Jianbo
Publikováno v:
Hangkong gongcheng jinzhan, Vol 10, Iss 4, Pp 496-504 (2019)
Currently, a set of scientific, systematical quality competitiveness evaluation system are lacked in our country, which is applied to aviation equipment, including aircraft, engines and missiles repair factory.The system engineering theory and proces
Externí odkaz:
https://doaj.org/article/10eb3765338a43a1878e930bdcee15bc
Publikováno v:
Hangkong gongcheng jinzhan, Vol 11, Iss 6, Pp 774-780,788 (2020)
Cloud operation is a new operational mode brought by cloud computing technology in the military field. In the future aviation and space information confrontation, cloud operation will have the invisible power application and the combination of virtua
Externí odkaz:
https://doaj.org/article/3304d7822df04dc1903fd52eabb55d4d
Improving the efficiency of current neural networks and modeling them in biological neural systems have become popular research directions in recent years. Pulse-coupled neural network (PCNN) is a well applicated model for imitating the computation c
Externí odkaz:
http://arxiv.org/abs/2403.17512
Autor:
Liu, Bingqi, Liao-McPherson, Dominic
In this paper, we propose an equilibrium-seeking algorithm for finding generalized Nash equilibria of non-cooperative monotone convex quadratic games. Specifically, we recast the Nash equilibrium-seeking problem as variational inequality problem that
Externí odkaz:
http://arxiv.org/abs/2403.13290
Autor:
Niu, Haoyi, Ji, Tianying, Liu, Bingqi, Zhao, Haocheng, Zhu, Xiangyu, Zheng, Jianying, Huang, Pengfei, Zhou, Guyue, Hu, Jianming, Zhan, Xianyuan
Solving real-world complex tasks using reinforcement learning (RL) without high-fidelity simulation environments or large amounts of offline data can be quite challenging. Online RL agents trained in imperfect simulation environments can suffer from
Externí odkaz:
http://arxiv.org/abs/2309.12716
Autor:
Liu, Bingqi1,2 (AUTHOR) liubingqi@cdu.edu.cn, Mo, Peijun1 (AUTHOR) mopeijun@stu.cdut.edu.cn, Wang, Shengzhe1 (AUTHOR), Cui, Yuyong1 (AUTHOR), Wu, Zhongjian1 (AUTHOR)
Publikováno v:
Sensors (14248220). Nov2024, Vol. 24 Issue 22, p7166. 22p.
Publikováno v:
In Finance Research Letters July 2024 65
Akademický článek
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Autor:
Buccino, Federica, Aiazzi, Irene, Casto, Alessandro, Liu, Bingqi, Sbarra, Maria Chiara, Ziarelli, Giovanni, Banfi, Giuseppe, Vergani, Laura Maria
Publikováno v:
In Journal of the Mechanical Behavior of Biomedical Materials January 2023 137