Zobrazeno 1 - 10
of 580
pro vyhledávání: '"hyper‐parameter optimization"'
Autor:
Abbas Jafar, Myungho Lee
Publikováno v:
IEEE Access, Vol 12, Pp 122942-122958 (2024)
Recently, the world has been dealing with a severe outbreak of COVID-19. The rapid transmission of the virus causes mild to severe cases of cough, fever, body aches, organ failures, and death. An increasing number of patients, fewer diagnostic option
Externí odkaz:
https://doaj.org/article/5da1a67e3d184e239c2c36a76d2cf1d7
Autor:
Majid Kundroo, Taehong Kim
Publikováno v:
IEEE Access, Vol 12, Pp 120570-120583 (2024)
Federated Learning (FL) has emerged as a promising paradigm for privacy-preserving distributed Machine Learning (ML), enabling model training across distributed devices without compromising data privacy. However, the impact of hyper-parameters on FL
Externí odkaz:
https://doaj.org/article/5dc68bc92d5d4cea8071df07565162d9
Publikováno v:
Energies, Vol 17, Iss 17, p 4434 (2024)
To enhance the stability of photovoltaic power grid integration and improve power prediction accuracy, a photovoltaic power prediction method based on an improved snow ablation optimization algorithm (Good Point and Vibration Snow Ablation Optimizer,
Externí odkaz:
https://doaj.org/article/b9ff042745d74833814816e3c1a32dfb
Autor:
Reddy, Shiva Sumanth, Nandini, C.
Publikováno v:
International Journal of Intelligent Computing and Cybernetics, 2022, Vol. 16, Issue 4, pp. 649-664.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJICC-11-2021-0260
Autor:
Muhamad Fajri, Aji Primajaya
Publikováno v:
Journal of Applied Informatics and Computing, Vol 7, Iss 1, Pp 10-15 (2023)
Classification is one of the important tasks in the field of Machine Learning. Classification can be viewed as an Optimization Problem (Optimization Problem) with the aim of finding the best model that can represent the relationship/pattern between d
Externí odkaz:
https://doaj.org/article/4fec4663dade4912bcc2cd45a790a09c
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
In this paper, the self-attention layer of a graph convolutional neural network is first constructed to output the important information in the network structure. The migration learning network model is established, and the sample data are preprocess
Externí odkaz:
https://doaj.org/article/8d0f92b64db74d9089d56305810896fd
Autor:
Muhammad Hanif Tunio, Jian Ping Li, Xiaoyang Zeng, Faijan Akhtar, Syed Attique Shah, Awais Ahmed, Yu Yang, Md Belal Bin Heyat
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 36, Iss 1, Pp 101895- (2024)
Accurate pre-harvest crop yield estimation is vital for agricultural sustainability and economic stability. The existing yield estimating models exhibit deficiencies in insufficient examination of hyperparameters, lack of robustness, restricted trans
Externí odkaz:
https://doaj.org/article/07bd931b5c7440f3a187892f75a1a3d8
Autor:
Aryan Salvati, Alireza Moghaddam Nia, Ali Salajegheh, Kayvan Ghaderi, Dawood Talebpour Asl, Nadhir Al‐Ansari, Feridon Solaimani, John J. Clague
Publikováno v:
Journal of Flood Risk Management, Vol 16, Iss 4, Pp n/a-n/a (2023)
Abstract Floods are both complex and destructive, and in most parts of the world cause injury, death, loss of agricultural land, and social disruption. Flood susceptibility (FS) maps are used by land‐use managers and land owners to identify areas t
Externí odkaz:
https://doaj.org/article/2fdb66acc03548c4b77339307ee6cc73
Autor:
Md. Jamal Uddin, Jitang Fan
Publikováno v:
Polymers, Vol 16, Iss 8, p 1049 (2024)
The glass transition temperature of polymers is a key parameter in meeting the application requirements for energy absorption. Previous studies have provided some data from slow, expensive trial-and-error procedures. By recognizing these data, machin
Externí odkaz:
https://doaj.org/article/983cf926fabe4916b57c190a95bef6f7
Autor:
Majid Kundroo, Taehong Kim
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 35, Iss 9, Pp 101740- (2023)
Federated Learning is a new approach for distributed training of a deep learning model on data scattered across a large number of clients while ensuring data privacy. However, this approach faces certain limitations, including a longer convergence ti
Externí odkaz:
https://doaj.org/article/e442a4582c5a4b4b96b3782b3fa863f1