抄録
We developed a model for predicting thermal sensation using a neural network (NN) considering secondary comfort factors. This study revealed the following three main points. 1. The prediction accuracy of the NN model is higher than that of the PMV, and the accuracy is also higher for naturally ventilated conditions. 2. Although ventilation condition improves the prediction accuracy, this effect disappears when considering outdoor and climatic factors. 3. While personal factors of age and gender and seasonal factors of date and season improve prediction accuracy, they have little power on prediction when considering climate and other factors.
寄稿の翻訳タイトル | THERMAL SENSATION PREDICTION USING NEURAL NETWORK CONSIDERING SECONDARY COMFORT FACTORS |
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本文言語 | 日本語 |
ページ(範囲) | 742-749 |
ページ数 | 8 |
ジャーナル | Journal of Environmental Engineering (Japan) |
巻 | 87 |
号 | 801 |
DOI | |
出版ステータス | 出版済み - 2022 |
!!!All Science Journal Classification (ASJC) codes
- 環境工学