Zobrazeno 1 - 10
of 1 119
pro vyhledávání: '"ZHANG Dongxiao"'
Publikováno v:
Xibei Gongye Daxue Xuebao, Vol 42, Iss 1, Pp 18-27 (2024)
Based on the volume of fluid multiphase flow model and the overset mesh technique, a numerical method for an asynchronous parallel oblique water-entry super-cavitating projectile was established. Experimental studies of the oblique water-entry of a h
Externí odkaz:
https://doaj.org/article/b9b197b49b714883b06919e1f93fb3d5
Autor:
Chen, Dayin, Shi, Xiaodan, Jiang, Mingkun, Zhang, Haoran, Zhang, Dongxiao, Chen, Yuntian, Yan, Jinyue
Photovoltaic power forecasting (PVPF) is a critical area in time series forecasting (TSF), enabling the efficient utilization of solar energy. With advancements in machine learning and deep learning, various models have been applied to PVPF tasks. Ho
Externí odkaz:
http://arxiv.org/abs/2408.00601
Autor:
Ma, Longfei, Cheng, Nan, Wang, Xiucheng, Chen, Jiong, Gao, Yinjun, Zhang, Dongxiao, Zhang, Jun-Jie
The development of Digital Twins (DTs) represents a transformative advance for simulating and optimizing complex systems in a controlled digital space. Despite their potential, the challenge of constructing DTs that accurately replicate and predict t
Externí odkaz:
http://arxiv.org/abs/2406.13145
Autor:
Xu, Lei, Chen, Yulong, Chen, Yuntian, Nie, Longfeng, Wei, Xuetao, Xue, Liang, Zhang, Dongxiao
Machine learning models offer the capability to forecast future energy production or consumption and infer essential unknown variables from existing data. However, legal and policy constraints within specific energy sectors render the data sensitive,
Externí odkaz:
http://arxiv.org/abs/2406.04743
Maximizing storage performance in geological carbon storage (GCS) is crucial for commercial deployment, but traditional optimization demands resource-intensive simulations, posing computational challenges. This study introduces the multimodal latent
Externí odkaz:
http://arxiv.org/abs/2406.04575
Autor:
Zhang, Yongan, Zhao, Junfeng, Li, Jian, Wang, Xuanran, Sun, Youzhuang, Chen, Yuntian, Zhang, Dongxiao
The prediction of formation resistivity plays a crucial role in the evaluation of oil and gas reservoirs, identification and assessment of geothermal energy resources, groundwater detection and monitoring, and carbon capture and storage. However, tra
Externí odkaz:
http://arxiv.org/abs/2406.03849
Photovoltaic (PV) power forecasting plays a crucial role in optimizing the operation and planning of PV systems, thereby enabling efficient energy management and grid integration. However, un certainties caused by fluctuating weather conditions and c
Externí odkaz:
http://arxiv.org/abs/2406.03808
Autor:
Cao, Qinglong, Chen, Yuntian, Lu, Lu, Sun, Hao, Zeng, Zhenzhong, Yang, Xiaokang, Zhang, Dongxiao
Large-scale Vision-Language Models (VLMs) have demonstrated exceptional performance in natural vision tasks, motivating researchers across domains to explore domain-specific VLMs. However, the construction of powerful domain-specific VLMs demands vas
Externí odkaz:
http://arxiv.org/abs/2405.08668
Equation discovery is aimed at directly extracting physical laws from data and has emerged as a pivotal research domain. Previous methods based on symbolic mathematics have achieved substantial advancements, but often require the design of implementa
Externí odkaz:
http://arxiv.org/abs/2405.07761
Autor:
Chen, Dayin, Shi, Xiaodan, Zhang, Haoran, Song, Xuan, Zhang, Dongxiao, Chen, Yuntian, Yan, Jinyue
Publikováno v:
IEEE Transactions on Mobile Computing,13 May 2024, 1 - 13
Enhancing the energy efficiency of buildings significantly relies on monitoring indoor ambient temperature. The potential limitations of conventional temperature measurement techniques, together with the omnipresence of smartphones, have redirected r
Externí odkaz:
http://arxiv.org/abs/2404.10401