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Thermal Comfort Modeling For Smart Buildings: A Fine-Grained Deep Learning Approach by Patriche Răzvan is a document available to read on EtoBox.

This document discusses using deep learning to develop accurate thermal comfort models for smart buildings. It proposes a fine-grained deep learning approach with separate models for individual comfort factors like temperature, and then combining them to determine overall comfort. The approach is tested using building IoT data and is found to outperform other machine learning methods.

Author
Patriche Răzvan
Language
EN