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- Title
A complete online-SVM pipeline for case-based reasoning system: a study on pipe defect detection system.
- Authors
Le, D. Van-Khoa; Chen, Zhiyuan; Wong, Yee Wan; Isa, Dino
- Abstract
Recent developments in case-based reasoning system (CBR) have led to an interest in favoring machine learning (ML) approaches as a replacement for traditional weighted distance methods. However, valuable information obtained through a training process was relinquished as transferring to other phases. This paper proposed a complete pipeline integration of CBR using kernel method designated with support vector machine (SVM) as the main engine. Since the system requires learning SVM model to be invoked in every phase, the online learning mechanism is nominated to effectively update the model when a new case adjoins. The proposed full SVM-CBR integration has been successfully built into a pipe defect detection. The achieved result indicates a substantial improvement by transferring learning information accurately.
- Subjects
CASE-based reasoning; BUILDING failures; SUPPORT vector machines; PIPELINES; MAGNETIC flux leakage; PIPE
- Publication
Soft Computing - A Fusion of Foundations, Methodologies & Applications, 2020, Vol 24, Issue 22, p16917
- ISSN
1432-7643
- Publication type
Article
- DOI
10.1007/s00500-020-04985-7