Predicting indoor temperature distribution with low data dependency using recurrent neural networks

Accurately predicting indoor temperature distribution can provide valuable reference data, helping residents independently adjust HVAC equipment around them to ensure comfort while reducing unnecessary energy consumption. This study proposes a prediction framework composed of two neural networks, en...

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Bibliographic Details
Main Authors: Jiahe Wang, Shohei Miyata, Keiichiro Taniguchi, Yasunori Akashi
Format: Article
Language:English
Published: Taylor & Francis Group 2025-03-01
Series:Journal of Asian Architecture and Building Engineering
Subjects:
Online Access:http://dx.doi.org/10.1080/13467581.2025.2474818
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