Zobrazeno 1 - 10
of 8 838
pro vyhledávání: '"data generation"'
Autor:
Vasileios C. Pezoulas, Dimitrios I. Zaridis, Eugenia Mylona, Christos Androutsos, Kosmas Apostolidis, Nikolaos S. Tachos, Dimitrios I. Fotiadis
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 2892-2910 (2024)
Synthetic data generation has emerged as a promising solution to overcome the challenges which are posed by data scarcity and privacy concerns, as well as, to address the need for training artificial intelligence (AI) algorithms on unbiased data with
Externí odkaz:
https://doaj.org/article/1595553cc13b4b048a4661b05bb4ccd8
Autor:
Divas Karimanzira
Publikováno v:
Stats, Vol 7, Iss 3, Pp 808-826 (2024)
The lack of data on flood events poses challenges in flood management. In this paper, we propose a novel approach to enhance flood-forecasting models by utilizing the capabilities of Generative Adversarial Networks (GANs) to generate synthetic flood
Externí odkaz:
https://doaj.org/article/8f62aa436bff4e3fa93bc3fccbf35506
Publikováno v:
Commodities, Vol 3, Iss 3, Pp 254-280 (2024)
The dynamic structure of electricity markets, where uncertainties abound due to, e.g., demand variations and renewable energy intermittency, poses challenges for market participants. We propose generative adversarial networks (GANs) to generate synth
Externí odkaz:
https://doaj.org/article/9af5f9b153794fc99f0f46805e97cc97
Autor:
Nicolas Alexander Schulz, Jasmin Carus, Alexander Johannes Wiederhold, Ole Johanns, Frederik Peters, Natalie Rath, Katharina Rausch, Bernd Holleczek, Alexander Katalinic, the AI-CARE Working Group, Christopher Gundler
Publikováno v:
BMC Medical Research Methodology, Vol 24, Iss 1, Pp 1-13 (2024)
Abstract Background Generating synthetic patient data is crucial for medical research, but common approaches build up on black-box models which do not allow for expert verification or intervention. We propose a highly available method which enables s
Externí odkaz:
https://doaj.org/article/dec1b1d848d74098abd187748b4ee6cc
Publikováno v:
Promet (Zagreb), Vol 36, Iss 3, Pp 560-579 (2024)
According to the current research status of urban rail transit’s fully automatic operation (FAO), the train driving speed curves are usually obtained through simulation and calculation. The train driving speed curves obtained by this method not onl
Externí odkaz:
https://doaj.org/article/dfc2548570df4136a53a077bf295790b
Synthetic data at scale: a development model to efficiently leverage machine learning in agriculture
Autor:
Jonathan Klein, Rebekah Waller, Sören Pirk, Wojtek Pałubicki, Mark Tester, Dominik L. Michels
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
The rise of artificial intelligence (AI) and in particular modern machine learning (ML) algorithms during the last decade has been met with great interest in the agricultural industry. While undisputedly powerful, their main drawback remains the need
Externí odkaz:
https://doaj.org/article/010dc692ab344e669ef051dcda21008f
Autor:
Daniar Aizhulov, Maksat Kurmanseiit, Nurlan Shayakhmetov, Madina Tungatarova, Ainur Suleimenova
Publikováno v:
Scientific Journal of Astana IT University, Pp 5-15 (2024)
The work presents an approach to enhance the forecasting capabilities of In-Situ Leaching processes during both the production stage and early prognosis. ISL, a crucial method for resource extraction, demands rapid on-site forecasting to guide the de
Externí odkaz:
https://doaj.org/article/5c899cf102404dc48c1f9bfae0cbe16f
Publikováno v:
Journal of Asian Architecture and Building Engineering, Vol 23, Iss 2, Pp 725-739 (2024)
While implementing a construction project, production-rate assessment needs to be conducted throughout the different stages of the project because this assessment can determine the success or failure of the project. In South Korea, the construction-s
Externí odkaz:
https://doaj.org/article/848e1d871aa74a3f8c15cfae1fa42473
Autor:
Charlotte Jamotton, Donatien Hainaut
Publikováno v:
Intelligent Systems with Applications, Vol 24, Iss , Pp 200455- (2024)
This article explores the application of Variational AutoEncoders (VAEs) to insurance data. Previous research has demonstrated the successful implementation of generative models, especially VAEs, across various domains, such as image recognition, tex
Externí odkaz:
https://doaj.org/article/a7dc249cff694ebda650880954d12a41
Publikováno v:
International Journal of Qualitative Studies on Health & Well-Being, Vol 19, Iss 1 (2024)
Purpose To describe how Qualitative Meaning Analysis (QMA), based on a lifeworld theoretical approach, can be made accessible to students and researchers not well-versed in the philosophy of science or qualitative research. Additionally, to demonstra
Externí odkaz:
https://doaj.org/article/01ccaeebbba541339cfe303883b625a2