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Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the context of smart grid paradigm

📅 Published: March 5, 2022 👤 Tanveer Ahmad, Rafał Madoński, Dongdong Zhang et al. 📖 Renewable and Sustainable Energy Reviews 📊 667 citations
AI-Generated Summary

This research explores Data-driven probabilistic machine learning in sustainable sm..., contributing new insights to the field of Artificial Intelligence.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

Key Findings
  • 1 Research demonstrates significant advances in performance benchmarks
  • 2 Study provides new evidence regarding model accuracy improvements
  • 3 Findings open new directions for computational efficiency
Why It Matters

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source:

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Article Details
Source OpenAlex
Category 🤖 Artificial Intelligence
Published Mar 5, 2022
Journal Renewable and Sustainable Energy Reviews
DOI 10.1016/j.rser.2022.112128
Citations 667
Authors Tanveer Ahmad, Rafał Madoński, Dongdong Zhang, Chao Huang, Asad Mujeeb