An ensemble hybrid and explainable AI (XAI) framework for zero false-positive islanding detection in distribution networks
- DOI
- 10.1038/s41598-026-43913-x
- Published
- 2026-03-13
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-43913-x,
title = {An ensemble hybrid and explainable AI (XAI) framework for zero false-positive islanding detection in distribution networks},
author = {Samiksha K. Shahade and Anjali U. Jawadekar and Aniket K. Shahade},
year = {2026},
journal = {Scientific Reports},
doi = {10.1038/s41598-026-43913-x},
url = {https://doi.org/10.1038/s41598-026-43913-x}
}RIS
TY - JOUR TI - An ensemble hybrid and explainable AI (XAI) framework for zero false-positive islanding detection in distribution networks AU - Samiksha K. Shahade AU - Anjali U. Jawadekar AU - Aniket K. Shahade PY - 2026 JO - Scientific Reports DO - 10.1038/s41598-026-43913-x UR - https://doi.org/10.1038/s41598-026-43913-x ER -
APA
Shahade, S. K., Jawadekar, A. U., & Shahade, A. K. (2026). An ensemble hybrid and explainable AI (XAI) framework for zero false-positive islanding detection in distribution networks. Scientific Reports. https://doi.org/10.1038/s41598-026-43913-x
Source records
- crossref · retrieved 2026-09-25T23:57:33.540Z