| A review of data-driven fault detection and diagnostics for building HVAC systems Z Chen, Z O’Neill, J Wen, O Pradhan, T Yang, X Lu, G Lin, S Miyata, S Lee, ... Applied Energy 339, 121030, 2023 | 47 | 2023 |
| Fault detection and diagnosis for heat source system using convolutional neural network with imaged faulty behavior data S Miyata, J Lim, Y Akashi, Y Kuwahara, K Tanaka Science and Technology for the Built Environment 26 (1), 52-60, 2020 | 38 | 2020 |
| Interpretable deep learning models for hourly solar radiation prediction based on graph neural network and attention Y Gao, S Miyata, Y Akashi Applied Energy 321, 119288, 2022 | 33 | 2022 |
| Operational optimization for off-grid renewable building energy system using deep reinforcement learning Y Gao, Y Matsunami, S Miyata, Y Akashi Applied Energy 325, 119783, 2022 | 32 | 2022 |
| Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives H Li, H Johra, F de Andrade Pereira, T Hong, J Le Dréau, A Maturo, ... Applied Energy 343, 121217, 2023 | 25 | 2023 |
| Multi-step solar irradiation prediction based on weather forecast and generative deep learning model Y Gao, S Miyata, Y Akashi Renewable Energy 188, 637-650, 2022 | 18 | 2022 |
| Methodology of evaluating the sewage heat utilization potential by modelling the urban sewage state prediction model WA Chen, J Lim, S Miyata, Y Akashi Sustainable Cities and Society 80, 103751, 2022 | 16 | 2022 |
| Energy saving and indoor temperature control for an office building using tube-based robust model predictive control Y Gao, S Miyata, Y Akashi Applied Energy 341, 121106, 2023 | 13 | 2023 |
| Multi-agent reinforcement learning dealing with hybrid action spaces: A case study for off-grid oriented renewable building energy system Y Gao, Y Matsunami, S Miyata, Y Akashi Applied Energy 326, 120021, 2022 | 13 | 2022 |
| Model predictive control of a building renewable energy system based on a long short-term hybrid model Y Gao, Y Matsunami, S Miyata, Y Akashi Sustainable Cities and Society 89, 104317, 2023 | 12 | 2023 |
| Model-based fault detection and diagnosis for HVAC systems using convolutional neural network S Miyata, Y Akashi, J Lim, Y Kuwahara, K Tanaka Proceedings of the Building Simulation Conference Proceedings, International …, 2019 | 9 | 2019 |
| How to improve the application potential of deep learning model in HVAC fault diagnosis: Based on pruning and interpretable deep learning method Y Gao, S Miyata, Y Akashi Applied Energy 348, 121591, 2023 | 8 | 2023 |
| 動的 CO2 排出係数に基づいたモデル予測制御による熱源機器の低炭素制御 宮田翔平， 桑原康浩， 林鍾衍， 赤司泰義， 吉本尚起 日本建築学会環境系論文集 85 (777), 827-835, 2020 | 5 | 2020 |
| Model-based fault detection and diagnosis using convolutional neural networks in heat source system with water thermal storage tanks S Miyata, Y Akashi, J Lim, K Tanaka, S Tanaka, Y Kuwahara IOP Conference Series: Earth and Environmental Science 238 (1), 012070, 2019 | 5 | 2019 |
| Spatio-temporal interpretable neural network for solar irradiation prediction using transformer Y Gao, S Miyata, Y Matsunami, Y Akashi Energy and Buildings 297, 113461, 2023 | 4 | 2023 |
| Successful application of predictive information in deep reinforcement learning control: A case study based on an office building HVAC system Y Gao, S Shi, S Miyata, Y Akashi Energy 291, 130344, 2024 | 3 | 2024 |
| Improving training efficiency for scalable automated fault detection and diagnosis in chilled water plants by transfer learning S Miyata, Y Kuwahara, S Tsunemoto, K Tanaka, Y Akashi Energy and Buildings 285, 112877, 2023 | 3 | 2023 |
| Optimal set-point regulation in HVAC system for controllability and energy efficiency S Miyata, J Lim, Y Akashi, Y Kuwahara Advances in Building Energy Research 14 (2), 160-170, 2020 | 3 | 2020 |
| Fault evaluation process in HVAC system for decision making of how to respond to system faults A Motomura, S Miyata, S Adachi, Y Akashi, J Lim, K Tanaka, Y Kuwahara IOP Conference Series: Earth and Environmental Science 294 (1), 012054, 2019 | 3 | 2019 |
| Fault Detection and Diagnosis in Building Heat Source Systems Using Machine Learning Part1―Fault Database Creation Using Simulation and Application of Convolutional Neural … S Miyata, Y Akashi, J Lim, Y Wu, K Tanaka, S Tanaka, Y Kuwahara Transactions of the Society of Heating, Air-conditioning and Sanitary …, 2018 | 3 | 2018 |
Jongyeon LimKangwon National University確認したメール アドレス: kangwon.ac.kr
