Zobrazeno 1 - 10
of 1 581
pro vyhledávání: '"SUN, Zhigang"'
Autor:
Wen, Dong, Liu, Zhongpei, Yang, Tong, Li, Tao, Li, Tianyun, Li, Chenglong, Li, Jie, Sun, Zhigang
Neural-networks-driven intelligent data-plane (NN-driven IDP) is becoming an emerging topic for excellent accuracy and high performance. Meanwhile we argue that NN-driven IDP should satisfy three design goals: the flexibility to support various NNs m
Externí odkaz:
http://arxiv.org/abs/2411.00408
Accurate trajectory prediction is crucial for ensuring safe and efficient autonomous driving. However, most existing methods overlook complex interactions between traffic participants that often govern their future trajectories. In this paper, we pro
Externí odkaz:
http://arxiv.org/abs/2405.03809
Trajectory prediction in autonomous driving relies on accurate representation of all relevant contexts of the driving scene, including traffic participants, road topology, traffic signs, as well as their semantic relations to each other. Despite incr
Externí odkaz:
http://arxiv.org/abs/2404.19379
Autor:
Jiang, Xuyan, Yang, Xiangrui, Zhou, Tongqing, Fu, Wenwen, Quan, Wei, Jiao, Yihao, Sun, Yinhan, Sun, Zhigang
Time-Sensitive Networking (TSN) is an emerging real-time Ethernet technology that provides deterministic communication for time-critical traffic. At its core, TSN relies on Time-Aware Shaper (TAS) for pre-allocating frames in specific time intervals
Externí odkaz:
http://arxiv.org/abs/2403.01652
Autor:
Mlodzian, Leon, Sun, Zhigang, Berkemeyer, Hendrik, Monka, Sebastian, Wang, Zixu, Dietze, Stefan, Halilaj, Lavdim, Luettin, Juergen
Trajectory prediction in traffic scenes involves accurately forecasting the behaviour of surrounding vehicles. To achieve this objective it is crucial to consider contextual information, including the driving path of vehicles, road topology, lane div
Externí odkaz:
http://arxiv.org/abs/2312.09676
Publikováno v:
Youqi dizhi yu caishoulu, Vol 31, Iss 6, Pp 160-167 (2024)
In view of the difficulties in formation energy replenishment and failed injection and production by water drive in low-permeability reservoirs， Shengli Oilfield proposed a water injection technology based on pressure drive for low-permeability res
Externí odkaz:
https://doaj.org/article/32e29033de7244ee9ffeeedec1cc03e4
Deep learning (DL) for network models have achieved excellent performance in the field and are becoming a promising component in future intelligent network system. Programmable in-network computing device has great potential to deploy DL for network
Externí odkaz:
http://arxiv.org/abs/2308.11312
Publikováno v:
Tongxin xuebao, Vol 45, Pp 1-13 (2024)
Aiming at the problems of existing time synchronization accuracy measurement methods based on clock pulse, such as complex measurement system composition, limited measurement scale by the number of instrument acquisition interfaces, and inability of
Externí odkaz:
https://doaj.org/article/6ef11777c566434782ee6a3518c625cc
Autor:
YANG Yong, ZHANG Shiming, LÜ Qi, SUN Zhigang, JIANG Long, SUN Hongxia, LIU Zupeng, LÜ Jing, XING Xiangdong, NI Liangtian
Publikováno v:
Youqi dizhi yu caishoulu, Vol 31, Iss 5, Pp 1-15 (2024)
The shale oil in the continental faulted basins in eastern China，represented by Jiyang shale oil，has made a breakthrough in production capacity. However，Jiyang shale oil faces great challenges in achieving high and stable production due to the
Externí odkaz:
https://doaj.org/article/3b27e5a7d0fb4d819bd2dc8597c1bab5
Autor:
SUN Zhigang, YU Chunlei, CHEN Hui, ZHANG Min, SUN Qiang, JIA Lihua, SUN Chao, CHEN Ting, ZHANG Hongxin, FAN Fei, ZHANG Lizhen
Publikováno v:
Youqi dizhi yu caishoulu, Vol 31, Iss 5, Pp 186-198 (2024)
As shale oil exploration and development intensifies， the experimental technologies for shale oil development have been continuously improved while inheriting the experimental technologies and methods of conventional reservoirs and shale gas reserv
Externí odkaz:
https://doaj.org/article/3a120efc343c48f2984bab645067baf5