| 1 |
Gradient boosting machine for modeling the energy consumption of commercial buildings
Touzani S, Granderson J, Fernandes S
Energy and Buildings, 158, 1533, 2018 |
| 2 |
The suitability of machine learning to minimise uncertainty in the measurement and verification of energy savings
Gallagher CV, Bruton K, Leahy K, O'Sullivan DTJ
Energy and Buildings, 158, 647, 2018 |
| 3 |
Cloud computing platform for real-time measurement and verification of energy performance
Ke MT, Yeh CH, Su CJ
Applied Energy, 188, 497, 2017 |
| 4 |
Low-cost energy meter calibration method for measurement and verification
Carstens H, Xia XH, Yadavalli S
Applied Energy, 188, 563, 2017 |
| 5 |
Application of automated measurement and verification to utility energy efficiency program data
Granderson J, Touzani S, Fernandes S, Taylor C
Energy and Buildings, 142, 191, 2017 |
| 6 |
Efficient longitudinal population survival survey sampling for the measurement and verification of lighting retrofit projects
Carstens H, Xia XH, Yadavalli S, Rajan A
Energy and Buildings, 150, 163, 2017 |
| 7 |
Evaluation of the renovation of a Danish single-family house based on measurements
Bjorneboe MG, Svendsen S, Heller A
Energy and Buildings, 150, 189, 2017 |
| 8 |
Efficient metering and surveying sampling designs in longitudinal Measurement and Verification for lighting retrofit
Carstens H, Xia XH, Yadavalli S
Energy and Buildings, 154, 430, 2017 |
| 9 |
Simplified field measurement and verification of global solar transmittance for glazing samples under natural clear-sky conditions
Song S, Haberl JS
Solar Energy, 155, 706, 2017 |
| 10 |
Accuracy of automated measurement and verification (M&V) techniques for energy savings in commercial buildings
Granderson J, Touzani S, Custodio C, Sohn MD, Jump D, Fernandes S
Applied Energy, 173, 296, 2016 |
