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A Chebyshev Polynomial‐Based Wind Speed Profile Characterization Framework: Applications in Mesoscale Model Evaluation

open access: yesWind Energy, Volume 29, Issue 2, February 2026.
ABSTRACT This study presents a polynomial‐based wind speed profile characterization framework that approximates full vertical profiles using five physically meaningful Chebyshev polynomial coefficients. The framework captures key morphological features of wind profiles, including mean wind speed, vertical shear, curvature, inflection‐related behavior ...
Harish Baki, Sukanta Basu
wiley   +1 more source

Forecasting the Rate of Induced Seismicity as a Neural Temporal Point Process

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 1, February 2026.
Abstract Forecasting is an essential part of risk mitigation, where the mitigation efficacy depends strongly on the quality of forecasts. We explore the neural temporal point process as a deep learning framework to forecast induced earthquakes. We train our deep learning model using numerous enhanced geothermal systems and hydraulic fracturing test ...
Ryan Schultz, Stefan Wiemer
wiley   +1 more source

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