2026-07-14 09:16 |
[FZJ-2026-03446]
Abstract
Kelp, M. ; Hickman, S. ; Miyazaki, K. ; et al
AI4O3: A Foundational Data Collection for Artificial Intelligence in Tropospheric Ozone Research
2025AI for Science Workshop at NeurIPS 2025, NeurIPS 2025, Mexico CityMexico City, Mexico, 30 Nov 2025 - 5 Dec 20252025-11-302025-12-05
[10.34734/FZJ-2026-03446]
Ozone (O3) is an internationally regulated air pollutant that damages human health, vegetation, and the climate, yet remains one of the most challenging atmospheric constituents to predict. Tropospheric ozone is driven by complex, nonlinear interactions between precursor emissions, meteorology, and chemistry across scales. [...]
OpenAccess: PDF; External link: Fulltext
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2026-06-30 12:25 |
[FZJ-2026-03200]
Abstract
Kleinebrahm, M. ; Weinand, J. ; Eiser, P. ; et al
A Benchmark Arena for Real-Time Energy Forecasting
2026EEM26 Conference, TrondheimTrondheim, Norway, 22 Jun 2026 - 24 Jun 20262026-06-222026-06-24
Forecasting electricity prices, load, and renewable generation has become essential for powersystem operators, energy traders, and analysts as renewable penetration and market volatility riseacross Europe, a trend reflected in the sharp growth of related research, including more than 4,000papers published in 2024 alone1. Despite a vast body of literature and notable open-access effortssuch as Lago et al.2 (2021), the field lacks a widely accepted, continuously updated real-timebenchmark that captures the evolving conditions of modern power markets. [...]
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2026-06-29 11:59 |
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