Approximating the universal thermal climate index using sparse regression with orthogonal polynomials
PositiveArtificial Intelligence
This article presents innovative methods for approximating the Universal Thermal Climate Index (UTCI), which is crucial for understanding thermal comfort in varying atmospheric conditions. By utilizing symbolic and sparse regression techniques, the research aims to enhance the interpretability and efficiency of function approximation for this important metric. This work is significant as it could lead to better assessments of thermal comfort, impacting fields like urban planning and climate adaptation.
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