A review of data-driven building energy consumption prediction studies K Amasyali, NM El-Gohary Renewable and Sustainable Energy Reviews, 2018 | 1641 | 2018 |
Intelligent multi-zone residential HVAC control strategy based on deep reinforcement learning Y Du, H Zandi, O Kotevska, K Kurte, J Munk, K Amasyali, E Mckee, F Li Applied Energy 281, 116117, 2020 | 189 | 2020 |
Machine learning for occupant-behavior-sensitive cooling energy consumption prediction in office buildings K Amasyali, N El-Gohary Renewable and Sustainable Energy Reviews 142, 110714, 2021 | 134 | 2021 |
Energy-related values and satisfaction levels of residential and office building occupants K Amasyali, NM El-Gohary Building and Environment 95, 251-263, 2016 | 85 | 2016 |
Building Lighting Energy Consumption Prediction for Supporting Energy Data Analytics K Amasyali, N El-Gohary Procedia Engineering 145, 511-517, 2016 | 63 | 2016 |
Multi-task deep reinforcement learning for intelligent multi-zone residential HVAC control Y Du, F Li, J Munk, K Kurte, O Kotevska, K Amasyali, H Zandi Electric Power Systems Research 192, 106959, 2021 | 56 | 2021 |
A comparison study on trading behavior and profit distribution in local energy transaction games Y Chen, B Park, X Kou, M Hu, J Dong, F Li, K Amasyali, M Olama Applied Energy 280, 115941, 2020 | 50 | 2020 |
Real data-driven occupant-behavior optimization for reduced energy consumption and improved comfort K Amasyali, NM El-Gohary Applied Energy 302, 117276, 2021 | 46 | 2021 |
Ten questions concerning reinforcement learning for building energy management Z Nagy, G Henze, S Dey, J Arroyo, L Helsen, X Zhang, B Chen, ... Building and Environment 241, 110435, 2023 | 35 | 2023 |
Evaluating the Adaptability of Reinforcement Learning Based HVAC Control for Residential Houses K Kurte, J Munk, O Kotevska, K Amasyali, R Smith, E McKee, Y Du, B Cui, ... Sustainability 12 (18), 7727, 2020 | 33 | 2020 |
Deep Learning for Building Energy Consumption Prediction K Amasyali, N El-Gohary 6th CSCE/CRC International Construction Specialty Conference, 2017 | 27 | 2017 |
Deep Reinforcement Learning for Autonomous Water Heater Control K Amasyali, J Munk, K Kurte, T Kuruganti, H Zandi Buildings 11 (11), 548, 2021 | 20 | 2021 |
Hybrid approach for energy consumption prediction: Coupling data-driven and physical approaches K Amasyali, N El-Gohary Energy and Buildings 259, 111758, 2022 | 18 | 2022 |
Hierarchical Model-Free Transactional Control of Building Loads to Support Grid Services K Amasyali, Y Chen, B Telsang, M Olama, SM Djouadi IEEE Access 8, 219367-219377, 2020 | 18 | 2020 |
Occupants’ Perceptions about Indoor Environment Comfort and Energy Related Values in Commercial and Residential Buildings Z Zhao, K Amasyali, R Chamoun, N El-Gohary Procedia Environmental Sciences 34, 631-640, 2016 | 17 | 2016 |
Methodology for Interpretable Reinforcement Learning Model for HVAC Energy Control O Kotevska, J Munk, K Kurte, Y Du, K Amasyali, RW Smith, H Zandi 2020 IEEE International Conference on Big Data (Big Data), 1555-1564, 2020 | 16 | 2020 |
Predicting energy consumption of office buildings: a hybrid machine learning-based approach K Amasyali, N El-Gohary Advances in Informatics and Computing in Civil and Construction Engineering …, 2019 | 11 | 2019 |
Comparative analysis of model-free and model-based HVAC control for residential demand response K Kurte, K Amasyali, J Munk, H Zandi Proceedings of the 8th ACM International Conference on Systems for Energy …, 2021 | 10 | 2021 |
A Machine Learning-based Approach to Predict the Aggregate Flexibility of HVAC Systems K Amasyali, M Olama, A Perumalla 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies …, 2020 | 10 | 2020 |
Power allocation by load aggregator with heterogeneous loads using weighted projection B Telsang, K Amasyali, Y Chen, M Olama, S Djouadi Energy and Buildings 244, 110955, 2021 | 9 | 2021 |