機械学習による空調負荷予測手法に関する研究
Abstract
<p>In this study, we investigated the optimal machine learning algorithm for predicting the air conditioning load of an office building. Predictions were made by the Gradient Boosting Decision Tree (GBDT), Deep Neural Network (DNN), Long Short Term Memory (LSTM), Last Query Transformer RNN (LQT) using air conditioning load and meteorological data for about two years.</p>
Journal
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- Techinical Papers of Annual Meeting the Society of Heating,Air-conditioning and Sanitary Engineers of Japan
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Techinical Papers of Annual Meeting the Society of Heating,Air-conditioning and Sanitary Engineers of Japan 2022.5 (0), 81-84, 2022
The Society of Heating,Air-Conditioning&Sanitary Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390579399399054592
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- ISSN
- 24242179
- 18803806
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- Text Lang
- ja
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- Data Source
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- JaLC
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- Abstract License Flag
- Disallowed