Stebėti
Chirag Deb
Chirag Deb
The University of Sydney
Patvirtintas el. paštas sydney.edu.au
Pavadinimas
Cituota
Cituota
Metai
A review on time series forecasting techniques for building energy consumption
C Deb, F Zhang, J Yang, SE Lee, KW Shah
Renewable and Sustainable Energy Reviews 74, 902-924, 2017
10922017
Time series forecasting for building energy consumption using weighted Support Vector Regression with differential evolution optimization technique
F Zhang, C Deb, SE Lee, J Yang, KW Shah
Energy and Buildings 126, 94-103, 2016
3452016
Forecasting diurnal cooling energy load for institutional buildings using Artificial Neural Networks
C Deb, LS Eang, J Yang, M Santamouris
Energy and Buildings 121, 284-297, 2016
3252016
k-Shape clustering algorithm for building energy usage patterns analysis and forecasting model accuracy improvement
J Yang, C Ning, C Deb, F Zhang, D Cheong, SE Lee, C Sekhar, KW Tham
Energy and Buildings 146, 27-37, 2017
1972017
Review of data-driven energy modelling techniques for building retrofit
C Deb, A Schlueter
Renewable and Sustainable Energy Reviews 144, 110990, 2021
1572021
Determining key variables influencing energy consumption in office buildings through cluster analysis of pre-and post-retrofit building data
C Deb, SE Lee
Energy and Buildings 159, 228-245, 2018
1322018
PV (photovoltaics) performance evaluation and simulation-based energy yield prediction for tropical buildings
EM Saber, SE Lee, S Manthapuri, W Yi, C Deb
Energy 71, 588-595, 2014
1202014
Evaluation of thermal comfort in a rail terminal location in India
C Deb, A Ramachandraiah
Building and Environment 45 (11), 2571-2580, 2010
1112010
The significance of physiological equivalent temperature (PET) in outdoor thermal comfort studies
C Deb, A Ramachandraiah
International Journal of Engineering Science and Technology 2 (7), 2825-2828, 2010
972010
Do energy performance certificates allow reliable predictions of actual energy consumption and savings? Learning from the Swiss national database
S Cozza, J Chambers, C Deb, JL Scartezzini, A Schlüter, MK Patel
Energy and Buildings 224, 110235, 2020
952020
Unsupervised learning of energy signatures to identify the heating system and building type using smart meter data
P Westermann, C Deb, A Schlueter, R Evins
Applied Energy 264, 114715, 2020
942020
Using artificial neural networks to assess HVAC related energy saving in retrofitted office buildings
C Deb, SE Lee, M Santamouris
Solar Energy 163, 32-44, 2018
922018
Energy performance model development and occupancy number identification of institutional buildings
J Yang, M Santamouris, SE Lee, C Deb
Energy and Buildings 123, 192-204, 2016
712016
Forecasting energy consumption of institutional buildings in Singapore
C Deb, LS Eang, J Yang, M Santamouris
Procedia Engineering 121, 1734-1740, 2015
592015
Envelope design for low-energy buildings in the tropics: A review
V Gupta, C Deb
Renewable and Sustainable Energy Reviews 186, 113650, 2023
572023
Wireless sensor network for estimating building performance
M Frei, C Deb, R Stadler, Z Nagy, A Schlueter
Automation in Construction 111, 103043, 2020
572020
A simplified tool for building layout design based on thermal comfort simulations
P Anand, C Deb, R Alur
Frontiers of Architectural Research 6 (2), 218-230, 2017
572017
Occupancy-based energy consumption modelling using machine learning algorithms for institutional buildings
P Anand, C Deb, K Yan, J Yang, D Cheong, C Sekhar
Energy and Buildings 252, 111478, 2021
562021
A machine learning-based framework for cost-optimal building retrofit
C Deb, Z Dai, A Schlueter
Applied energy 294, 116990, 2021
402021
Early-stage design support combining machine learning and building information modelling
MM Singh, C Deb, P Geyer
Automation in Construction 136, 104147, 2022
392022
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Straipsniai 1–20