| A review of artificial intelligence based building energy use prediction: Contrasting the capabilities of single and ensemble prediction models Z Wang, RS Srinivasan Renewable and Sustainable Energy Reviews 75, 796-808, 2017 | 713 | 2017 |
| Adopting Internet of Things for the development of smart buildings: A review of enabling technologies and applications M Jia, A Komeily, Y Wang, RS Srinivasan Automation in Construction 101, 111-126, 2019 | 623 | 2019 |
| Random Forest based hourly building energy prediction Z Wang, Y Wang, R Zeng, RS Srinivasan, S Ahrentzen Energy and Buildings 171, 11-25, 2018 | 582 | 2018 |
| Smart cities: foundations, principles, and applications H Song, R Srinivasan, T Sookoor, S Jeschke John Wiley & Sons, 2017 | 364 | 2017 |
| From occupancy to occupant behavior: An analytical survey of data acquisition technologies, modeling methodologies and simulation coupling mechanisms for building energy efficiency M Jia, RS Srinivasan, AA Raheem Renewable and Sustainable Energy Reviews 68, 525-540, 2017 | 308 | 2017 |
| A need for balanced approach to neighborhood sustainability assessments: A critical review and analysis A Komeily, RS Srinivasan Sustainable Cities and Society 18, 32-43, 2015 | 260 | 2015 |
| Machine learning applications in urban building energy performance forecasting: A systematic review S Fathi, R Srinivasan, A Fenner, S Fathi Renewable and Sustainable Energy Reviews 133, 110287, 2020 | 254 | 2020 |
| A novel ensemble learning approach to support building energy use prediction Z Wang, Y Wang, RS Srinivasan Energy and Buildings 159, 109-122, 2018 | 205 | 2018 |
| Re (De) fining net zero energy: renewable emergy balance in environmental building design RS Srinivasan, WW Braham, DE Campbell, CD Curcija Building and Environment 47, 300-315, 2012 | 159 | 2012 |
| A new paradigm for Human-Building Interaction: the use of CFD and Augmented Reality AM Malkawi, RS Srinivasan Automation in construction 14 (1), 71-84, 2005 | 147 | 2005 |
| Applying blockchain technology for building energy performance measurement, reporting, and verification (MRV) and the carbon credit market: A review of the literature J Woo, R Fatima, CJ Kibert, RE Newman, Y Tian, RS Srinivasan Building and Environment 205, 108199, 2021 | 139 | 2021 |
| A systematic review of air quality sensors, guidelines, and measurement studies for indoor air quality management H Zhang, R Srinivasan Sustainability 12 (21), 9045, 2020 | 113 | 2020 |
| Practical issues in implementing machine-learning models for building energy efficiency: Moving beyond obstacles Z Wang, J Liu, Y Zhang, H Yuan, R Zhang, RS Srinivasan Renewable and Sustainable Energy Reviews 143, 110929, 2021 | 110 | 2021 |
| Comparison of energy-based indicators used in life cycle assessment tools for buildings RS Srinivasan, W Ingwersen, C Trucco, R Ries, D Campbell Building and environment 79, 138-151, 2014 | 110 | 2014 |
| An integrated energy–emergy approach to building form optimization: Use of EnergyPlus, emergy analysis and Taguchi-regression method H Yi, RS Srinivasan, WW Braham Building and Environment 84, 89-104, 2015 | 88 | 2015 |
| Energy use assessment of educational buildings: Toward a campus-wide sustainable energy policy D Agdas, RS Srinivasan, K Frost, FJ Masters Sustainable Cities and Society 17, 15-21, 2015 | 84 | 2015 |
| A review of artificial intelligence based building energy prediction with a focus on ensemble prediction models Z Wang, RS Srinivasan 2015 Winter simulation conference (WSC), 3438-3448, 2015 | 82 | 2015 |
| Low cost, multi-pollutant sensing system using raspberry pi for indoor air quality monitoring H Zhang, R Srinivasan, V Ganesan Sustainability 13 (1), 370, 2021 | 79 | 2021 |
| An ecological understanding of net-zero energy building: Evaluation of sustainability based on emergy theory H Yi, RS Srinivasan, WW Braham, DR Tilley Journal of Cleaner Production 143, 654-671, 2017 | 70 | 2017 |
| Decision support and design evolution: integrating genetic algorithms, CFD and visualization AM Malkawi, RS Srinivasan, KY Yun, R Choudhary Automation in construction 14 (1), 33-44, 2005 | 63 | 2005 |
Zeyu WangGuangzhou University, University of FloridaZweryfikowany adres z gzhu.edu.cn
