Zobrazeno 1 - 10
of 6 519
pro vyhledávání: '"Qin Yan"'
Recent advancements in sensor technology and deep learning have led to significant progress in 3D human body reconstruction. However, most existing approaches rely on data from a specific sensor, which can be unreliable due to the inherent limitation
Externí odkaz:
http://arxiv.org/abs/2409.04851
Publikováno v:
Journal of Energy Storage, Volume 100, Part A, 15 October 2024, 113502
Data-driven methods have gained extensive attention in estimating the state of health (SOH) of lithium-ion batteries. Accurate SOH estimation requires degradation-relevant features and alignment of statistical distributions between training and testi
Externí odkaz:
http://arxiv.org/abs/2409.00141
In this work, we consider a state estimation problem for large-scale nonlinear processes in the absence of first-principles process models. By exploiting process operation data, both process modeling and state estimation design are addressed within a
Externí odkaz:
http://arxiv.org/abs/2404.06746
In this paper, partition-based distributed state estimation of general linear systems is considered. A distributed moving horizon state estimation scheme is developed via decomposing the entire system model into subsystem models and partitioning the
Externí odkaz:
http://arxiv.org/abs/2404.06706
Putting a price on carbon -- with taxes or developing carbon markets -- is a widely used policy measure to achieve the target of net-zero emissions by 2050. This paper tackles the issue of producing point, direction-of-change, and density forecasts f
Externí odkaz:
http://arxiv.org/abs/2402.04828
By informing the onset of the degradation process, health status evaluation serves as a significant preliminary step for reliable remaining useful life (RUL) estimation of complex equipment. This paper proposes a novel temporal dynamics learning-base
Externí odkaz:
http://arxiv.org/abs/2401.04351
Data-driven soft sensors provide a potentially cost-effective and more accurate modeling approach to measure difficult-to-measure indices in industrial processes compared to mechanistic approaches. Artificial intelligence (AI) techniques, such as dee
Externí odkaz:
http://arxiv.org/abs/2312.12022
Autor:
Haoyu Qiu, Qin Yan, Yuchuan Yang, Xu Huang, Jinmei Wang, Jiajie Luo, Lang Peng, Ge Bai, Liuyue Zhang, Rui Zhang, Yongshuo H. Fu, Chaoyang Wu, Josep Peñuelas, Lei Chen
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-11 (2024)
Abstract Late spring frosts, occurring after spring phenological events, pose a dire threat to tree growth and forest productivity. With climate warming, earlier spring phenological events have become increasingly common and led to plants experiencin
Externí odkaz:
https://doaj.org/article/844e8c7c58804b3ea0a3332d0623025e
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-8 (2024)
Abstract Evaluate the real-world effectiveness and safety of different treatment regimens for treatment-naïve high viral load chronic hepatitis B (CHB) patients. Between January 2021 and August 2022, CHB patients with HBV DNA ≥ 107 IU/mL were coll
Externí odkaz:
https://doaj.org/article/b19859d2ffe1460597d3cfc0cbfe5658
Publikováno v:
Aeecpted by IEEE TASE 2023
Data-driven industrial health prognostics require rich training data to develop accurate and reliable predictive models. However, stringent data privacy laws and the abundance of edge industrial data necessitate decentralized data utilization. Thus,
Externí odkaz:
http://arxiv.org/abs/2305.07854