Publication2022
A review on application of Machine Learning in Solar Energy Photovoltaic Generation Prediction
The record
- Type
- Publication
- Date
- 1 January 2022
- Level
- National
- Journal
- Proceedings of the International Conference on Electronics and Renewable Systems Icears 2022
- Pages
- 1180-1184
- Published
- 1 January 2022
- DOI
- 10.1109/icears53579.2022.9752404
- Scopus ID
- 85128926337
- Authors
- 6
- Open access
- No
- Citations
- 28
- 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
Review of machine learning applications for photovoltaic power generation forecasting demonstrates AI techniques for predicting solar irradiance and optimizing renewable energy grid integration.
- 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
Machine learning for renewable energy forecasting advances green energy transition through improved solar power prediction and grid management efficiency.
- 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 Machine Learning in Solar Energy Photovoltaic Generation Prediction”. Kortex.