Conference Editor

Jianshun Zhang; Edward Bogucz; Cliff Davidson; Elizabeth Krietmeyer

Keywords:

Indoor environment, Model training, Data collection, Air temperature, Relative humidity

Location

Syracuse, NY

Event Website

http://ibpc2018.org/

Start Date

24-9-2018 3:30 PM

End Date

24-9-2018 5:00 PM

Description

It is important to create comfortable indoor environments for building occupants. This study developed neural network (NN) models for predicting thermal comfort in indoor environments by using thermal sensations and occupants’ behavior. The models were trained by data on air temperature, relative humidity, clothing insulation, metabolic rate, thermal sensations, and occupants’ behavior collected in ten offices. The models were able to predict similar acceptable air temperature ranges in offices, from 20.6℃ to 25℃ in winter and from 20.6℃ to 25.6℃ in summer. The comfort zone obtained by the NN model using thermal sensations in the ten offices was narrower than the comfort zone in ASHRAE Standard 55, but that obtained by the NN model using behaviors was wider than the ASHRAE comfort zone. This investigation demonstrates alternative approaches to the prediction of thermal comfort.

Comments

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DOI

https://doi.org/10.14305/ibpc.2018.hf-1.04

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.

COinS
 
Sep 24th, 3:30 PM Sep 24th, 5:00 PM

Neural Network Models Using Thermal Sensations and Occupants’ Behavior for Predicting Thermal Comfort

Syracuse, NY

It is important to create comfortable indoor environments for building occupants. This study developed neural network (NN) models for predicting thermal comfort in indoor environments by using thermal sensations and occupants’ behavior. The models were trained by data on air temperature, relative humidity, clothing insulation, metabolic rate, thermal sensations, and occupants’ behavior collected in ten offices. The models were able to predict similar acceptable air temperature ranges in offices, from 20.6℃ to 25℃ in winter and from 20.6℃ to 25.6℃ in summer. The comfort zone obtained by the NN model using thermal sensations in the ten offices was narrower than the comfort zone in ASHRAE Standard 55, but that obtained by the NN model using behaviors was wider than the ASHRAE comfort zone. This investigation demonstrates alternative approaches to the prediction of thermal comfort.

https://surface.syr.edu/ibpc/2018/HF1/4

 

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