Publication2025
An Intelligent CNN-LSTM Based Framework for Multi-Class Insulator Fault Diagnosis in High-Voltage Transmission Systems
The record
- Type
- Publication
- Date
- 1 January 2025
- Level
- National
- Journal
- 2025 IEEE 4th World Conference on Applied Intelligence and Computing Aic 2025
- Pages
- 197-202
- Published
- 1 January 2025
- DOI
- 10.1109/aic66080.2025.11212127
- Scopus ID
- 105023639243
- Authors
- 3
- Open access
- No
- Citations
- 2
- 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
7.1 Ensure universal access to affordable, reliable and modern energy services
CNN-LSTM framework for insulator fault detection ensures reliable high-voltage transmission system operation supporting electricity service continuity
- 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
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Deep learning research advances AI application in power system monitoring and predictive fault diagnostics
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2.4 Infrastructure and connectivity
Infrastructure and connectivity research improving power system reliability for consistent electricity access
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
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- 1
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Citing this record
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KIIT Deemed to be University. “An Intelligent CNN-LSTM Based Framework for Multi-Class Insulator Fault Diagnosis in High-Voltage Transmission Systems”. Kortex.