Código QR (código de barras bidimensional)

Physics-Aligned Data Augmentation for Reliable Property Prediction in Direct Ink Writing Under Extreme Data Scarcity

Reliable property prediction in extrusion-based additive manufacturing remains challenging under extreme data scarcity (e.g., sample size of <50), particularly when experiments are constrained by designed studies such as Taguchi orthogonal arrays. In direct ink writing of lignocellulosic composites,...

Fuld beskrivelse

Na minha lista:
Principais autores: Biva Gyawali, Pavan Akula, Kamran Alba, Vahid Nasir
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2026-03-01
Serier:Journal of Manufacturing and Materials Processing
Fag:
data-driven additive manufacturing
synthetic data augmentation
direct ink writing (DIW)
explainable machine learning
variational autoencoder
generative adversarial network (GAN)
Online adgang:https://www.mdpi.com/2504-4494/10/4/118
Tags: Tilføj Tag
Ingen Tags, Vær først til at tagge denne postø!

Lignende værker