Design and Modeling of Intelligent Building Office and Thermal Comfort Based on Probabilistic Neural Network
Author:
Funder
Silesian University of Technology
Universitá di Catania
Publisher
Springer Science and Business Media LLC
Subject
General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s42979-022-01411-7.pdf
Reference34 articles.
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4. Jung W, Jazizadeh F. Energy saving potentials of integrating personal thermal comfort models for control of building systems: comprehensive quantification through combinatorial consideration of influential parameters. Appl Energy. 2020;268: 114882.
5. Kang M, Kim KR, Lee J-Y, Shin J-Y. Determination of thermal sensation levels for Koreans based on perceived temperature and climate chamber experiments with hot and humid settings. Int J Biometeorol. 2022;66:1095–107.
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