Zobrazeno 1 - 10
of 8 683
pro vyhledávání: '"Wasserstein"'
Publikováno v:
IET Renewable Power Generation, Vol 18, Iss 16, Pp 3731-3742 (2024)
Abstract A novel Wasserstein generative adversarial network (WGAN) is proposed for stochastic wind power output scenario generation. Wasserstein distance with gradient penalty adapts to the gradient vanishing problem that is easy to occur in the new
Externí odkaz:
https://doaj.org/article/8e2d413f606d4c529a6575c1d42b279f
Publikováno v:
Nuclear Engineering and Technology, Vol 56, Iss 12, Pp 5055-5067 (2024)
Data-driven fault diagnosis techniques are significant for the stable operation of nuclear power plants (NPPs). However, in practical applications, the fault diagnosis of NPPs usually faces imbalance data problems with small fault samples and much re
Externí odkaz:
https://doaj.org/article/13a4f9f12164437590b388b183a89ccf
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract Credit scoring models are critical for financial institutions to assess borrower risk and maintain profitability. Although machine learning models have improved credit scoring accuracy, imbalanced class distributions remain a major challenge
Externí odkaz:
https://doaj.org/article/6f51d7d4f3b44c48a47e17c0fd3ddfc0
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract In data assimilation, observations are fused with simulations to obtain an accurate estimate of the state and parameters for a given physical system. Combining data with a model, however, while accurately estimating uncertainty, is computati
Externí odkaz:
https://doaj.org/article/0dc26924cfdc4bcb86b839a46a8f4f43
Publikováno v:
Energy Informatics, Vol 7, Iss 1, Pp 1-18 (2024)
Abstract The overall electricity consumption of electrolytic aluminum and ferroalloy loads is significant, and some of these loads have dispatch potential that can be used to locally absorb wind power while reducing dependence on conventional thermal
Externí odkaz:
https://doaj.org/article/eee50205bbea4b468f038dfaf4063c3c
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Large Language Models (LLMs), such as the General Pre-trained Transformer (GPT), have shown remarkable performance in various cognitive tasks. However, it remains unclear whether these models have the ability to accurately infer human percep
Externí odkaz:
https://doaj.org/article/d27be1417c5c4fdca5f177a1dbce6091
Autor:
Zhang, Kaiyi
Optimal Transport (OT), also known as Wasserstein distance, is a valuable metric for comparing probability distributions. Owing to its appealing statistical properties, researchers in various fields, such as machine learning, use OT within applicatio
Externí odkaz:
https://hdl.handle.net/10919/123647
