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Publication date: 2026-04-24
A benchmark-focused publication introducing methodology and evidence pathways for evaluating smart-grid forecasting models using BQEB-Data.
Zenodo
Preprint
Agrawal, R. K. (2026). BQEB ForecastBench: Benchmarking AI Models for Smart Grid Forecasting Using BQEB-Data v1. Zenodo. https://doi.org/10.5281/zenodo.19716383
@article{agrawal2026forecastbench, title={BQEB ForecastBench: Benchmarking AI Models for Smart Grid Forecasting Using BQEB-Data v1}, author={Agrawal, Rakesh Kumar}, journal={Zenodo}, year={2026}, doi={10.5281/zenodo.19716383}}research-portfolio
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View sourceRakeshKumarAgrawal.github.io
Personal portfolio repository showcasing enterprise AI research, platform engineering, cloud architecture, open-source projects, and technical publications.
View sourceBQEB-Data
Open benchmark dataset for autonomous energy intelligence and smart grid analytics.
View sourceBQEB ForecastBench
2026 | Zenodo | DOI 10.5281/zenodo.19716383
View sourceBQEB-Data: An Open Benchmark Dataset for Autonomous Energy Intelligence and Smart Grid Analytics
2026 | Zenodo | DOI 10.5281/zenodo.19656915
View sourceBQEB ForecastBench
Benchmarking AI models for smart grid forecasting using BQEB-Data v1.
View sourceBQEB-Data
Open benchmark dataset for autonomous energy intelligence and smart grid analytics.
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