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of 4
pro vyhledávání: '"EskandariNasab, MohammadReza"'
Current Generative Adversarial Network (GAN)-based approaches for time series generation face challenges such as suboptimal convergence, information loss in embedding spaces, and instability. To overcome these challenges, we introduce an advanced fra
Externí odkaz:
http://arxiv.org/abs/2410.21203
Accurate solar flare prediction is crucial due to the significant risks that intense solar flares pose to astronauts, space equipment, and satellite communication systems. Our research enhances solar flare prediction by utilizing advanced data prepro
Externí odkaz:
http://arxiv.org/abs/2409.14016
Generating time series data using Generative Adversarial Networks (GANs) presents several prevalent challenges, such as slow convergence, information loss in embedding spaces, instability, and performance variability depending on the series length. T
Externí odkaz:
http://arxiv.org/abs/2409.14013
Autor:
EskandariNasab, MohammadReza1 (AUTHOR) reza.eskandarinasab@usu.edu, Raeisi, Zahra2 (AUTHOR), Lashaki, Reza Ahmadi3 (AUTHOR), Najafi, Hamidreza4 (AUTHOR)
Publikováno v:
Scientific Reports. 4/17/2024, Vol. 14 Issue 1, p1-18. 18p.
