Thermal comfort evaluation within non-residential environments: Development of Artificial Neural Network by using the adaptive approach data

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Abstract

A new algorithm for the PMV calculation was developed using Artificial Neural Networks. Several experimental investigations were carried out in two classrooms using both Fanger static model and adaptive approaches for the PMV evaluation. The Artificial Neural Network was trained considering a few input parameters; specifically for the network development only the air temperature and relative humidity were considered as experimental data. This algorithm allows to correlate the thermal sensation to both indoor and outdoor factors and it is a useful tool for predicting the PMV index, replacing the traditional methods with less time and cost demanding.

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Buratti, C., Vergoni, M., & Palladino, D. (2015). Thermal comfort evaluation within non-residential environments: Development of Artificial Neural Network by using the adaptive approach data. In Energy Procedia (Vol. 78, pp. 2875–2880). Elsevier Ltd. https://doi.org/10.1016/j.egypro.2015.11.656

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