Study and Application of Industrial Thermal Comfort Parameters by Using Bayesian Inference Techniques

Study and Application of Industrial Thermal Comfort Parameters by Using Bayesian Inference Techniques

This paper focuses on the use of Bayesian networks for the industrial thermal comfort issue, specifically in industries in Northern Argentina. Mined data sets that are analyzed and exploited with WEKA and ELVIRA tools are discussed. Thus, networks giving the predictive value of thermal comfort for d...

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Bibliographic Details
Main Authors: Patricia I. Benito, Miguel A. Sebastián, Cristina González-Gaya
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Applied Sciences
Subjects:
thermal comfort
industrial building
occupational risk
Bayesian inference
sustainability
energy saving
Online Access:https://www.mdpi.com/2076-3417/11/24/11979

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