Publication2023
An Analysis of Machine Learning Methods for Electricity Price Forecasting
- Affordable and Clean Energy
- Industry, Innovation and Infrastructure
- Thriving and Sustainable Economy
The record
- Type
- Publication
- Date
- 1 January 2023
- Level
- National
- Journal
- 2023 1st International Conference on Circuits Power and Intelligent Systems Ccpis 2023
- Published
- 1 January 2023
- DOI
- 10.1109/ccpis59145.2023.10291210
- Scopus ID
- 85177564087
- Authors
- 3
- Open access
- No
- Citations
- 1
- 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
Comparative analysis of machine learning methods for short-term electricity price forecasting supports market decision-making in energy trading activities.
- 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.
- 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
Multiple regression analysis and machine learning model comparison advances research methodology in energy market forecasting.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2 Thriving and Sustainable Economy
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 7 label. Comparative analysis of machine learning methods for short-term electricity price forecasting supports market decision-making in energy trading activities.
- 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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Citing this record
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KIIT Deemed to be University. “An Analysis of Machine Learning Methods for Electricity Price Forecasting”. Kortex.