Machine learning approaches for resource management and forecasting in energy consumption systems
) of up to 0.988, whereas a two-stage AI framework integrating Markowitz-based portfolio optimization and energy-constrained battery control achieves an average variance reduction of 95.4% in grid stability.
Authors
- Ali Ghaffari (ORCID: https://orcid.org/0000-0001-5208-972X)
- Hesam Mohammad Asghari
Institutions
- Khazar University (AZ)
- Islamic Azad University of Tabriz (IR)
- Istinye University (TR)
Publication Details
- Journal
- Scientific Reports
- Published
- 2026-05-09
- DOI
- https://doi.org/10.1038/s41598-026-52189-0
- Primary Topic
- Energy Load and Power Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 0.00