| 1 |
Deep learning-based feature engineering methods for improved building energy prediction
Fan C, Sun YJ, Zhao Y, Song MJ, Wang JY
Applied Energy, 240, 35, 2019 |
| 2 |
A short-term building cooling load prediction method using deep learning algorithms
Fan C, Xiao F, Zhao Y
Applied Energy, 195, 222, 2017 |
| 3 |
Unsupervised energy prediction in a Smart Grid context using reinforcement cross-building transfer learning
Mocanu E, Nguyen PH, Kling WL, Gibescu M
Energy and Buildings, 116, 646, 2016 |
| 4 |
Building's electricity consumption prediction using optimized artificial neural networks and principal component analysis
Li KJ, Hu CL, Liu GH, Xue WP
Energy and Buildings, 108, 106, 2015 |
| 5 |
Development of prediction models for next-day building energy consumption and peak power demand using data Mining techniques
Fan C, Xiao F, Wang SW
Applied Energy, 127, 1, 2014 |
| 6 |
Pseudo dynamic transitional modeling of building heating energy demand using artificial neural network
Paudel S, Elmtiri M, Kling WL, Le Corre O, Lacarriere B
Energy and Buildings, 70, 81, 2014 |
| 7 |
Forecasting building energy consumption using neural networks and hybrid neuro-fuzzy system: A comparative study
Li KJ, Su HY, Chu J
Energy and Buildings, 43(10), 2893, 2011 |
| 8 |
Long-term energy demand predictions based on short-term measured data
Olofsson T, Andersson S
Energy and Buildings, 33(2), 85, 2001 |
