Multi-classifier information fusion in risk analysis
This paper develops a novel multi-classifier information fusion approach that integrates the probabilistic support vector machine (SVM) and the improved Dempster-Shafer (D-S) evidence theory to support risk analysis under uncertainty. Safety levels for various risk factors can be classified separate...
Saved in:
Main Authors: | Pan, Yue, Zhang, Limao, Wu, Xianguo, Skibniewski, Miroslaw J. |
---|---|
Other Authors: | School of Civil and Environmental Engineering |
Format: | Article |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/155275 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Cluster-based information fusion for probabilistic risk analysis in complex projects under uncertainty
by: Zhang, Limao, et al.
Published: (2022) -
Multi-source information fusion for safety risk assessment in underground tunnels
by: Guo, Kai, et al.
Published: (2022) -
Modeling face reliability in tunneling : a copula approach
by: Pan, Yue, et al.
Published: (2021) -
Clustering of designers based on building information modeling event logs
by: Pan, Yue, et al.
Published: (2022) -
Sensitivity analysis of structural health risk in operational tunnels
by: Liu, Wenli, et al.
Published: (2020)