Reconstruction of Missing Data Completely at Random for Trains Based on Improved GAN

Reconstruction of missing data for heavy-haul trains is critical to ensuring safe train operation. However, existing generative model training methods require a complete dataset, making it difficult for them to address the issue of missing data completely at random. To address this issue, this study...

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Vydané v:	Journal of advanced computational intelligence and intelligent informatics Ročník 29; číslo 5; s. 1068 - 1076
Hlavní autori:	He, Jing, Chen, Xin, Zhang, Changfan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Tokyo Fuji Technology Press Co. Ltd 20.09.2025
Predmet:	Feature extraction Generative adversarial networks Missing data Reconstruction
ISSN:	1343-0130, 1883-8014
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