Zobrazeno 1 - 10
of 25 325
pro vyhledávání: '"initialization"'
Autor:
F. F. Murzakhanov, G. V. Mamin, M. A. Sadovnikova, D. V. Shurtakova, O. P. Kazarova, E. N. Mokhov, M. R. Gafurov
Publikováno v:
Учёные записки Казанского университета. Серия Физико-математические науки, Vol 166, Iss 2, Pp 187-199 (2024)
Spin defects in semiconductors are attracting interest as a material basis for quantum information and computing technologies. In this work, the spin properties of negatively charged nitrogen-vacancy (NV−) centers in a 6H-SiC silicon carbide crysta
Externí odkaz:
https://doaj.org/article/625c55a4c65a4457b34dd55c88d80111
Publikováno v:
International Journal of Electrical Power & Energy Systems, Vol 161, Iss , Pp 110163- (2024)
This paper presents an accurate and efficient initialization strategy for modular multilevel converters (MMCs) based on the shooting method, a numerical technique aimed at deriving the periodic steady-state operating condition of any circuit. This te
Externí odkaz:
https://doaj.org/article/c4e69c90694e41b2a675ccc1d0805e50
Publikováno v:
Frontiers in Bioinformatics, Vol 4 (2024)
The application of quantum principles in computing has garnered interest since the 1980s. Today, this concept is not only theoretical, but we have the means to design and execute techniques that leverage the quantum principles to perform calculations
Externí odkaz:
https://doaj.org/article/b7b265e25bb74ecbabfa3a21d51d50f3
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 4, Pp 5331-5358 (2024)
Abstract Rough fuzzy clustering algorithms have received extensive attention due to the excellent ability to handle overlapping and uncertainty of data. However, existing rough fuzzy clustering algorithms generally consider single view clustering, wh
Externí odkaz:
https://doaj.org/article/ce1f1b470a8546af9f3c30621786c581
Publikováno v:
Geo-spatial Information Science, Pp 1-15 (2024)
ABSTRACTFor kinematic relative positioning users between two moving platforms, limited communication bandwidth and computation ability usually cannot support real-time transmission of high-rate (≥10 Hz) BeiDou Navigation Satellite System (BDS) data
Externí odkaz:
https://doaj.org/article/e8adfa51780c43da807017d62bf0f27f
Autor:
Safwan Mahmood Al-Selwi, Mohd Fadzil Hassan, Said Jadid Abdulkadir, Amgad Muneer, Ebrahim Hamid Sumiea, Alawi Alqushaibi, Mohammed Gamal Ragab
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 36, Iss 5, Pp 102068- (2024)
Long Short-Term Memory (LSTM) is a popular Recurrent Neural Network (RNN) algorithm known for its ability to effectively analyze and process sequential data with long-term dependencies. Despite its popularity, the challenge of effectively initializin
Externí odkaz:
https://doaj.org/article/27ee88a14cd54da4a23f266081f7f1a4
Autor:
R. W. Lee, A. J. Charlton‐Perez
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 10, Pp n/a-n/a (2024)
Abstract The stratosphere has previously been shown to be a significant source of subseasonal tropospheric predictability. The ability of ensemble prediction systems to appropriately exploit this depends on their ability to reproduce the statistical
Externí odkaz:
https://doaj.org/article/666a01f249374b169046dd9c0c2074ed
Publikováno v:
Frontiers in Human Neuroscience, Vol 18 (2024)
BackgroundChannel selection has become the pivotal issue affecting the widespread application of non-invasive brain-computer interface systems in the real world. However, constructing suitable multi-objective problem models alongside effective search
Externí odkaz:
https://doaj.org/article/1aeec931a5fa413a93de5b015c8591a3
Publikováno v:
Frontiers in Earth Science, Vol 12 (2024)
Tropical cyclone (TC) intensity forecasting poses challenges due to complex dynamical processes and data inadequacies during model initialization. This paper describes efforts to improve TC intensity prediction in the Geophysical Fluid Dynamics Labor
Externí odkaz:
https://doaj.org/article/bd0484da5d87430685ffc153673b742a
Publikováno v:
IEEE Access, Vol 12, Pp 115219-115236 (2024)
Recurrent Neural Networks (RNNs), including the distinguished Long Short-Term Memory Networks (LSTMs), have been shown to be effective in a wide range of sequential data problems. However, their ability to model very long-term dependencies still pose
Externí odkaz:
https://doaj.org/article/6a26aaa3b4b64cac9182debd99915649