This is a subset of the ASHRAE Global Comfort Database that we used in our study to prove that Deep learning methods performs better than shallow methods predicting the thermal sensation.

DOI Link: 
10.21227/9s4y-e116
Links or DOI: 
ASHRAE Global Thermal Comfort Database II
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Dataset Files

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[1] Mustafa Cakir, "Thermal Sensation", IEEE Dataport, 2021. [Online]. Available: http://dx.doi.org/10.21227/9s4y-e116. Accessed: Oct. 03, 2024.
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doi = {10.21227/9s4y-e116},
url = {http://dx.doi.org/10.21227/9s4y-e116},
author = {Mustafa Cakir },
publisher = {IEEE Dataport},
title = {Thermal Sensation},
year = {2021} }
TY - DATA
T1 - Thermal Sensation
AU - Mustafa Cakir
PY - 2021
PB - IEEE Dataport
UR - 10.21227/9s4y-e116
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Mustafa Cakir. (2021). Thermal Sensation. IEEE Dataport. http://dx.doi.org/10.21227/9s4y-e116
Mustafa Cakir, 2021. Thermal Sensation. Available at: http://dx.doi.org/10.21227/9s4y-e116.
Mustafa Cakir. (2021). "Thermal Sensation." Web.
1. Mustafa Cakir. Thermal Sensation [Internet]. IEEE Dataport; 2021. Available from : http://dx.doi.org/10.21227/9s4y-e116
Mustafa Cakir. "Thermal Sensation." doi: 10.21227/9s4y-e116