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| Creator | Title | Description | Subject | Date | ||
|---|---|---|---|---|---|---|
| 1 |
 | Rahman, Aowabin | Predicting heating demand and sizing a stratified thermal storage tank using deep learning algorithms | This paper evaluates the performance of deep recurrent neural networks in predicting heating demand for a commercial building over a medium-to-long term time horizon (≥ 1 week), and proposes a modeling framework to demonstrate how these longer-term predictions can be used to aid design of a strati... | Building Energy Modeling; Machine Learning; Recurrent Neural Networks; Deep Learning; Heating Load Prediction; Thermal Energy Storage | 2018 |
| 2 |
 | Legorburu, Gabriel | Energy modeling framework for optimizing heat recovery in a seasonal food processing facility | Societal, cultural and economic factors are driving food processors to reduce energy consumed per unit mass of food. This presents a unique problem because time variant batch processing using low to medium grade heat is common in food production facilities. Heat recovery methods may be implemented b... | Energy efficiency; Food industry; Heat recovery; Optimization; Simulation | 2018-07-20 |
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