| Deep-learning neural-network architectures and methods: Using component-based models in building-design energy prediction S Singaravel, J Suykens, P Geyer Advanced Engineering Informatics 38, 81-90, 2018 | 156 | 2018 |
| Component-oriented decomposition for multidisciplinary design optimization in building design P Geyer Advanced Engineering Informatics 23 (1), 12-31, 2009 | 144 | 2009 |
| Integrating requirement analysis and multi-objective optimization for office building energy retrofit strategies Y Shao, P Geyer, W Lang Energy and Buildings 82, 356-368, 2014 | 110 | 2014 |
| Systems modelling for sustainable building design P Geyer Advanced Engineering Informatics 26 (4), 656-668, 2012 | 83 | 2012 |
| Linking BIM and Design of Experiments to balance architectural and technical design factors for energy performance A Schlueter, P Geyer Automation in Construction 86, 33-43, 2018 | 74 | 2018 |
| Component-based machine learning for performance prediction in building design P Geyer, S Singaravel Applied energy 228, 1439-1453, 2018 | 72 | 2018 |
| Multidisciplinary grammars supporting design optimization of buildings P Geyer Research in Engineering Design 18 (4), 197-216, 2008 | 62 | 2008 |
| Automated metamodel generation for Design Space Exploration and decision-making–A novel method supporting performance-oriented building design and retrofitting P Geyer, A Schlüter Applied Energy 119, 537-556, 2014 | 59 | 2014 |
| Application of clustering for the development of retrofit strategies for large building stocks P Geyer, A Schlüter, S Cisar Advanced Engineering Informatics 31, 32-47, 2017 | 51 | 2017 |
| Simulation-based decision-making in early design stages F Ritter, P Geyer, A Borrmann 32nd CIB W78 Conference, Eindhoven, The Netherlands, 27-29, 2015 | 34 | 2015 |
| Uncertainty analysis of life cycle energy assessment in early stages of design H Harter, MM Singh, P Schneider-Marin, W Lang, P Geyer Energy and Buildings 208, 109635, 2020 | 30 | 2020 |
| Information requirements for multi-level-of-development BIM using sensitivity analysis for energy performance MM Singh, P Geyer Advanced Engineering Informatics 43, 101026, 2020 | 28 | 2020 |
| Quick energy prediction and comparison of options at the early design stage MM Singh, S Singaravel, R Klein, P Geyer Advanced Engineering Informatics 46, 101185, 2020 | 27 | 2020 |
| Consistent management and evaluation of building models in the early design stages J Abualdenien, P Schneider-Marin, A Zahedi, H Harter, H Exner, ... Journal of Information Technology in Construction 25, 212-232, 2020 | 25 | 2020 |
| Hybrid thermo-chemical district networks–Principles and technology P Geyer, M Buchholz, R Buchholz, M Provost Applied Energy 186, 480-491, 2017 | 25 | 2017 |
| Parametric systems modeling for sustainable energy and resource flows in buildings and their urban environment P Geyer, M Buchholz Automation in construction 22, 70-80, 2012 | 20 | 2012 |
| Deep convolutional learning for general early design stage prediction models S Singaravel, J Suykens, P Geyer Advanced Engineering Informatics 42, 100982, 2019 | 18 | 2019 |
| Component-based machine learning modelling approach for design stage building energy prediction: weather conditions and size S Singaravel, P Geyer, J Suykens Proceedings of the 15th IBPSA conference, 2617-2626, 2017 | 17 | 2017 |
| Component-based machine learning for energy performance prediction by MultiLOD models in the early phases of building design P Geyer, MM Singh, S Singaravel Advanced Computing Strategies for Engineering: 25th EG-ICE International …, 2018 | 14 | 2018 |
| Analysis of georeferenced building data for the identification and evaluation of thermal microgrids A Schlueter, P Geyer, S Cisar Proceedings of the IEEE 104 (4), 713-725, 2016 | 14 | 2016 |
