| 1 |
Decision tree for identification and prediction of filamentous bulking at full-scale activated sludge wastewater treatment plant
Deepnarain N, Nasr M, Kumari S, Stenstrom TA, Reddy P, Pillay K, Bux F
Process Safety and Environmental Protection, 126, 25, 2019 |
| 2 |
Approximate model predictive building control via machine learning
Drgona J, Picard D, Kvasnica M, Helsen L
Applied Energy, 218, 199, 2018 |
| 3 |
Temperature homogenization of a solar trough field for performance improvement
Sanchez AJ, Gallego AJ, Escano JM, Camacho EF
Solar Energy, 165, 1, 2018 |
| 4 |
A pattern recognition approach for modeling the air change rates in naturally ventilated buildings from limited steady-state CFD simulations
Mousa WAY, Lang W, Auer T, Yousef WA
Energy and Buildings, 155, 54, 2017 |
| 5 |
Multi-site solar power forecasting using gradient boosted regression trees
Persson C, Bacher P, Shiga T, Madsen H
Solar Energy, 150, 423, 2017 |
| 6 |
DR-Advisor: A data-driven demand, response recommender system
Behl M, Smarra F, Mangharam R
Applied Energy, 170, 30, 2016 |
| 7 |
Predicting future monthly residential energy consumption using building characteristics and climate data: A statistical learning approach
Williams KT, Gomez JD
Energy and Buildings, 128, 1, 2016 |
| 8 |
Prediction of steam-assisted gravity drainage steam to oil ratio from reservoir characteristics
Akbilgic O, Zhu D, Gates ID, Bergerson JA
Energy, 93, 1663, 2015 |
| 9 |
Local models-based regression trees for very short-term wind speed prediction
Troncoso A, Salcedo-Sanz S, Casanova-Mateo C, Riquelme JC, Prieto L
Renewable Energy, 81, 589, 2015 |
| 10 |
Miscanthus spatial location as seen by farmers: A machine learning approach to model real criteria
Rizzo D, Martin L, Wohlfahrt J
Biomass & Bioenergy, 66, 348, 2014 |
