Publication2021
Stockwell Transform & Data Mining based method for Fault detection and classification in PV Array
The record
- Type
- Publication
- Date
- 1 January 2021
- Level
- National
- Journal
- Proceedings of 2021 IEEE International Conference on Power Electrical Electronic and Industrial Applications Peeiacon 2021
- Pages
- 21-24
- Published
- 1 January 2021
- DOI
- 10.1109/peeiacon54708.2021.9929999
- Scopus ID
- 85142214719
- Authors
- 6
- Open access
- No
- Citations
- 5
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
7 Ensure access to affordable, reliable, sustainable and modern energy for all
Machine learning fault detection and classification in photovoltaic arrays using stockwell transform improves system reliability and prevents power loss.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2.5 Green economy, energy transition and climate resilience
PV array diagnostic technology supports renewable energy system efficiency and sustainability through fault prevention.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Stockwell Transform & Data Mining based method for Fault detection and classification in PV Array”. Kortex.