Predicting Commercial Building Energy Consumption Using a Multivariate Multilayered Long-Short Term Memory Time-Series Model
2023 · Applied Sciences · 16 citations
https://doi.org/10.3390/app13137775
T
Tan Ngoc Dinh
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Tan Ngoc Dinh is an academic researcher from Swinburne University of Technology. The author has contributed to research in topics: Building Energy and Comfort Optimization & Energy Load and Power Forecasting & Air Quality Monitoring and Forecasting. The author has an h-index of 3, co-authored 12 publications.
Papers by this author
worksPredicting Commercial Building Energy Consumption Using a Multivariate Multilayered Long-Short Term Memory Time-Series Model
2023 · Preprints.org · 8 citations
https://doi.org/10.20944/preprints202306.0135.v1
Robust-mv-M-LSTM-CI: Robust Energy Consumption Forecasting in Commercial Buildings during the COVID-19 Pandemic
2024 · Sustainability · 5 citations
https://doi.org/10.3390/su16156699
Bayesian Optimized of CNN-M-LSTM for Thermal Comfort Prediction and Load Forecasting in Commercial Buildings
2025 · Designs · 3 citations
https://doi.org/10.3390/designs9030069
Energy Consumption Forecasting in Commercial Buildings during the COVID-19 Pandemic: A Multivariate Multilayered Long-Short Term Memory Time-Series Model with Knowledge Injection
2023 · Sustainability · 3 citations
https://doi.org/10.3390/su151712951
State of Health Aware Adaptive Scheduling of Battery Energy Storage System Charging and Discharging in Rural Microgrids Using Long Short-Term Memory and Convolutional Neural Networks
2025 · Energies · 2 citations
https://doi.org/10.3390/en18215641
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