Thermal comfort evaluation using linear discriminant analysis (LDA) and artificial neural networks (ANNs)

16Citations
Citations of this article
29Readers
Mendeley users who have this article in their library.

Abstract

The thermal sensations of people differ from each other, even if they are in the same thermal conditions. The research was carried out in a didactic teaching room located in the building of the Faculty of Civil and Environmental Engineering in Poland. Tests on the temperature were carried out simultaneously with questionnaire surveys. The purpose of the survey was to define sensations regarding the thermal comfort of people in the same room, in different conditions of internal and external temperatures. In total 333 questionnaires were analyzed. After the discriminant and neural analyses it was found that it is not possible to forecast the thermal comfort assessment in the room based on the analyzed variables: gender, indoor air temperature, external wall radiant temperature, and outdoor air temperature. The thermal comfort assessments of men and women were similar and overlapped. The results of this study confirm that under the same thermal conditions about 85% of respondents assess thermal comfort as good, and about 15% of respondents assess thermal comfort as bad. The test results presented in this article are similar to the results of tests carried out by other authors in other climatic conditions.

Cite

CITATION STYLE

APA

Gładyszewska-Fiedoruk, K., & Sulewska, M. J. (2020). Thermal comfort evaluation using linear discriminant analysis (LDA) and artificial neural networks (ANNs). Energies, 13(3). https://doi.org/10.3390/en13030538

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free