Explainable Machine Learning for Multi-Class Power Quality Disturbance Classification Using SHAP and Feature Importance Analysis
- DOI
- 10.13140/rg.2.2.17883.43048
- Published
- 2026
- Container
- Not recorded
- Publisher
- Unpublished
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.13140/rg.2.2.17883.43048,
title = {Explainable Machine Learning for Multi-Class Power Quality Disturbance Classification Using SHAP and Feature Importance Analysis},
author = {Md Fujael Ahmed and Rashedul Albab and Md. Al Amin Chy and Ajijul Haque Sakib Opu and Tahsin, Abdul Hadee and Md.Tanvir Mahmud},
year = {2026},
doi = {10.13140/rg.2.2.17883.43048},
url = {https://doi.org/10.13140/rg.2.2.17883.43048}
}RIS
TY - JOUR TI - Explainable Machine Learning for Multi-Class Power Quality Disturbance Classification Using SHAP and Feature Importance Analysis AU - Md Fujael Ahmed AU - Rashedul Albab AU - Md. Al Amin Chy AU - Ajijul Haque Sakib Opu AU - Tahsin, Abdul Hadee AU - Md.Tanvir Mahmud PY - 2026 DO - 10.13140/rg.2.2.17883.43048 UR - https://doi.org/10.13140/rg.2.2.17883.43048 ER -
APA
Ahmed, M. F., Albab, R., Chy, M. A. A., Opu, A. H. S., Hadee, T. A., & Mahmud, M. (2026). Explainable Machine Learning for Multi-Class Power Quality Disturbance Classification Using SHAP and Feature Importance Analysis. https://doi.org/10.13140/rg.2.2.17883.43048
Source records
- datacite · retrieved 2026-09-25T01:26:40.588Z