Zobrazeno 1 - 10
of 677
pro vyhledávání: '"Gaussian process regression (GPR)"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Controlled release of a desired drug from porous polymeric biomaterials was analyzed via computational method. The method is based on simulation of mass transfer and utilization of artificial intelligence (AI). This study explores the effica
Externí odkaz:
https://doaj.org/article/41ad13b1e98b4780aabd80a3a0e6321b
Publikováno v:
International Journal of Transportation Science and Technology, Vol 15, Iss , Pp 244-259 (2024)
This study develops and evaluates models to estimate annual average daily traffic (AADT) at non-coverage or out-of-network locations. The non-coverage locations are those where counts are performed very infrequently, but an up-to-date and accurate es
Externí odkaz:
https://doaj.org/article/66eca2a9522644528434ac09027128c5
Publikováno v:
气体物理, Vol 9, Iss 4, Pp 27-38 (2024)
Since random uncertainty may cause severe aerodynamic performance fluctuations for the wing-mounted aircraft, the Gaussian process regression (GPR) surrogate model method based on was proposed. The strategy of adding sample points by active-learning
Externí odkaz:
https://doaj.org/article/ebf9c64c656e44d9a8b9fef78ea3b1b7
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract This study explores the potential of photocatalytic degradation using novel NML-BiFeO3 (noble metal-incorporated bismuth ferrite) compounds for eliminating malachite green (MG) dye from wastewater. The effectiveness of various Gaussian proce
Externí odkaz:
https://doaj.org/article/ea19f83faac5413190cd847a8ecac65d
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 17, Pp n/a-n/a (2024)
Abstract In Numerical Weather Prediction (NWP) models, such as the Weather Research and Forecasting (WRF) model, parameter uncertainty in physics parameterization schemes significantly impacts model output. Our study adopts a Bayesian probabilistic a
Externí odkaz:
https://doaj.org/article/e51459fc02f242aab4b9e477adf40815
Publikováno v:
CES Transactions on Electrical Machines and Systems, Vol 8, Iss 1, Pp 32-42 (2024)
The noise that comes from finite element simulation often causes the model to fall into the local optimal solution and over fitting during optimization of generator. Thus, this paper proposes a Gaussian Process Regression (GPR) model based on Conditi
Externí odkaz:
https://doaj.org/article/2fdf283119414c80b50e3702855c0f62
Autor:
Biswajit Bhagowati, Kamal Uddin Ahamad
Publikováno v:
Water Quality Research Journal, Vol 59, Iss 1, Pp 1-25 (2024)
Data-driven models for the prediction of lake eutrophication essentially rely on water quality datasets for a longer duration. If such data are not readily available, lake management through data-driven modeling becomes impractical. So, a novel appro
Externí odkaz:
https://doaj.org/article/4e35bbf7db94420db7f39c7f64a21d74
Publikováno v:
Journal of Modern Power Systems and Clean Energy, Vol 12, Iss 1, Pp 179-188 (2024)
Interval state estimation (ISE) can estimate state intervals of power systems according to confidence intervals of predicted pseudo-measurements, thereby analyzing the impact of uncertain pseudo-measurements on states. However, predicted pseudo-measu
Externí odkaz:
https://doaj.org/article/a98f5e12359d4aaaa8bf731dadbc827c
Autor:
Lai, Yangyang, Park, Seungbae
Publikováno v:
Soldering & Surface Mount Technology, 2023, Vol. 35, Issue 5, pp. 257-264.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/SSMT-03-2023-0013
Autor:
Eatidal Amin, Luca Pipia, Santiago Belda, Gregor Perich, Lukas Valentin Graf, Helge Aasen, Shari Van Wittenberghe, José Moreno, Jochem Verrelst
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 126, Iss , Pp 103636- (2024)
Precise knowledge of cropland productivity is relevant for farmers to enable optimizing managing practices; particularly with the perspective of anticipating crop yield ahead of harvest. The current availability of high spatiotemporal resolution Sent
Externí odkaz:
https://doaj.org/article/a8bb85440b7f41fb9a8aa795e47f6f54