A knowledge graph attention network for the cold‐start problem in intelligent manufacturing: Interpretability and accuracy improvement

A knowledge graph attention network for the cold‐start problem in intelligent manufacturing: Interpretability and accuracy improvement

Abstract In the rolling production of steel, predicting the performance of new products is challenging due to the low variety of data distributions resulting from standardized manufacturing processes and fixed product categories. This scenario poses a significant hurdle for machine learning models,...

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Bibliographic Details
Main Authors: Ziye Zhou, Yuqi Zhang, Shuize Wang, David San Martin, Yongqian Liu, Yang Liu, Chenchong Wang, Wei Xu
Format: Article
Language:English
Published: Wiley-VCH 2025-06-01
Series:Materials Genome Engineering Advances
Subjects:
attention mechanisms
cold‐start problem
graph neural network
interpretable machine learning
knowledge graph
materials design
Online Access:https://doi.org/10.1002/mgea.85
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