Publication2019
A Review on Application of ANN and Machine Learning Algorithm for the Optimal Placement of STATCOM
The record
- Type
- Publication
- Date
- 1 March 2019
- Level
- National
- Journal
- 2019 Innovations in Power and Advanced Computing Technologies I Pact 2019
- Published
- 1 March 2019
- DOI
- 10.1109/i-pact44901.2019.8960138
- Scopus ID
- 85078985179
- Authors
- 6
- Open access
- No
- Citations
- 7
- 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
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Machine learning and artificial neural network algorithms for optimal STATCOM placement advance computational methods for power system optimization.
- 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
7.1 Ensure universal access to affordable, reliable and modern energy services
STATCOM optimization improves reactive power management and voltage stability in power distribution networks.
- 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-2.5 Green economy, energy transition and climate resilience
Power system optimization enhances energy infrastructure efficiency and grid stability.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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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. “A Review on Application of ANN and Machine Learning Algorithm for the Optimal Placement of STATCOM”. Kortex.