1 |
Solar radiation prediction using recurrent neural network and artificial neural network: A case study with comparisons Pang ZH, Niu FX, O'Neill Z Renewable Energy, 156, 279, 2020 |
2 |
A review of smart building sensing system for better indoor environment control Dong B, Prakash V, Feng F, O'Neill Z Energy and Buildings, 199, 29, 2019 |
3 |
An innovative fault impact analysis framework for enhancing building operations Li YF, O'Neill Z Energy and Buildings, 199, 311, 2019 |
4 |
Nationwide savings analysis of energy conservation measures in buildings Qian DF, Li YF, Niu FX, O'Neill Z Energy Conversion and Management, 188, 1, 2019 |
5 |
Using change-point and Gaussian process models to create baseline energy models in industrial facilities: A comparison Carpenter J, Woodbury KA, O'Neill Z Applied Energy, 213, 415, 2018 |
6 |
Uncertainty quantification and sensitivity analysis of the domestic hot water usage in hotels Pang ZH, O'Neill Z Applied Energy, 232, 424, 2018 |
7 |
Change point and degree day baseline regression models in industrial facilities Golden A, Woodbury K, Carpenter J, O'Neill Z Energy and Buildings, 144, 30, 2017 |
8 |
Development of a probabilistic graphical model for predicting building energy performance O'Neill Z, O'Neill C Applied Energy, 164, 650, 2016 |
9 |
Evaluation of "Autotune" calibration against manual calibration of building energy models Chaudhary G, New J, Sanyal J, Im P, O'Neill Z, Garg V Applied Energy, 182, 115, 2016 |
10 |
Development and calibration of an online energy model for campus buildings Dong B, O'Neill Z, Luo D, Bailey T Energy and Buildings, 76, 316, 2014 |