Zobrazeno 1 - 10
of 892
pro vyhledávání: '"A. Andea"'
In recent years, deep learning-based solar forecasting using all-sky images has emerged as a promising approach for alleviating uncertainty in PV power generation. However, the stochastic nature of cloud movement remains a major challenge for accurat
Externí odkaz:
http://arxiv.org/abs/2306.11682
Sky-image-based solar forecasting using deep learning has been recognized as a promising approach in reducing the uncertainty in solar power generation. However, one of the biggest challenges is the lack of massive and diversified sky image samples.
Externí odkaz:
http://arxiv.org/abs/2211.14709
Autor:
Nie, Yuhao, Paletta, Quentin, Scott, Andea, Pomares, Luis Martin, Arbod, Guillaume, Sgouridis, Sgouris, Lasenby, Joan, Brandt, Adam
Solar forecasting from ground-based sky images has shown great promise in reducing the uncertainty in solar power generation. With more and more sky image datasets open sourced in recent years, the development of accurate and reliable deep learning-b
Externí odkaz:
http://arxiv.org/abs/2211.02108
Large-scale integration of photovoltaics (PV) into electricity grids is challenged by the intermittent nature of solar power. Sky-image-based solar forecasting using deep learning has been recognized as a promising approach to predicting the short-te
Externí odkaz:
http://arxiv.org/abs/2207.00913
Publikováno v:
Advances in Applied Energy, Vol 14, Iss , Pp 100172- (2024)
The variability of solar photovoltaic (PV) power output, driven by rapidly changing cloud dynamics, hinders the transition to reliable renewable energy systems. Information on future sky conditions, especially cloud coverage, holds the promise for im
Externí odkaz:
https://doaj.org/article/3224e1d0874049d5ac45899e009f8271
Autor:
Harms, Paul W., Runge, Mason, Chan, May P., Liu, Chia-Jen, Qin, Zhaoping, Worden, Francis, Robinson, Dan R., Chinnaiyan, Arul M., Mclean, Scott A., Harms, Kelly L., Fullen, Douglas R., Patel, Rajiv M., Andea, Aleodor A., Udager, Aaron M.
Publikováno v:
In Modern Pathology November 2024 37(11)
Autor:
Andea Ndari Marela, Lizar Alfansi
Publikováno v:
Manajemen dan Bisnis, Vol 23, Iss 1, Pp 13-32 (2024)
This research constitutes an innovative contribution by exploring Generation Z's inclination to subscribe to Netflix. As this demographic dominates streaming platforms, understanding factors influencing subscription willingness is crucial in the digi
Externí odkaz:
https://doaj.org/article/ef808e4a04a04213b55d02ac03cbdde3
Autor:
Nie, Yuhao, Paletta, Quentin, Scott, Andea, Pomares, Luis Martin, Arbod, Guillaume, Sgouridis, Sgouris, Lasenby, Joan, Brandt, Adam
Publikováno v:
In Applied Energy 1 September 2024 369
Publikováno v:
In Advances in Applied Energy July 2024 14
A data-driven and equation-free approach is proposed and discussed to model ships maneuvers in waves, based on the dynamic mode decomposition (DMD). DMD is a dimensionality-reduction/reduced-order modeling method, which provides a linear finite-dimen
Externí odkaz:
http://arxiv.org/abs/2105.13062