Research on risk assessment and optimization of GCN supply chain financial network based on M estimation
With rapid development of supply chain finance, risk assessment has become a key link to ensure financial security. Traditional methods make it difficult to assess risks in complex network environments. Therefore, this study proposes a graph convolutional network (GCN) model based on M estimation fo...
Saved in:
Main Authors: | Xinquan Yu, Feide Tong, Zhongzhen Hu |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-12-01
|
Series: | Systems and Soft Computing |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2772941925001462 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Financial Spillover Effects in Supply Chains: Do Customers and Suppliers Really Benefit?
by: Erik Hofmann, et al.
Published: (2020-03-01) -
Utilizing GCN-Based Deep Learning for Road Extraction from Remote Sensing Images
by: Yu Jiang, et al.
Published: (2025-06-01) -
CSC-GCN: Contrastive semantic calibration for graph convolution network
by: Xu Yang, et al.
Published: (2023-11-01) -
Modeling Supply Chain Finance Resilience with a Complex Adaptive SEIJR Framework
by: Yimeng Ye, et al.
Published: (2025-06-01) -
Knowledge Sharing in the Supply Chain Networks: A Perspective of Supply Chain Complexity Drivers
by: Hareer Fatima Ahmed, et al.
Published: (2022-09-01)