A dynamic anomaly detection method of building energy consumption based on data mining technology
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DOI: 10.1016/j.energy.2022.125575
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Cited by:
- Bartlomiej Kawa & Piotr Borkowski, 2023. "Integration of Machine Learning Solutions in the Building Automation System," Energies, MDPI, vol. 16(11), pages 1-18, June.
- Li, Xingwei & Huang, Yicheng, 2024. "Exploring the mechanisms affecting energy consumption in the construction industry using an integrated theoretical framework: Evidence from the Yangtze River economic Belt," Energy, Elsevier, vol. 299(C).
- Kim, Sungil & Kim, Tea-Woo & Hong, Yongjun & Kim, Juhyun & Jeong, Hoonyoung, 2024. "Enhancing pressure gradient prediction in multi-phase flow through diverse well geometries of North American shale gas fields using deep learning," Energy, Elsevier, vol. 290(C).
- Zhang, Chengyu & Rezgui, Yacine & Luo, Zhiwen & Jiang, Ben & Zhao, Tianyi, 2024. "Simultaneous community energy supply-demand optimization by microgrid operation scheduling optimization and occupant-oriented flexible energy-use regulation," Applied Energy, Elsevier, vol. 373(C).
- Thomas Wu & Bo Wang & Dongdong Zhang & Ziwei Zhao & Hongyu Zhu, 2023. "Benchmarking Evaluation of Building Energy Consumption Based on Data Mining," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
- Zhang, Limao & Guo, Jing & Lin, Penghui & Tiong, Robert L.K., 2025. "Detecting energy consumption anomalies with dynamic adaptive encoder-decoder deep learning networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 207(C).
- Yuping Zou & Rui Wu & Xuesong Tian & Hua Li, 2023. "Realizing the Improvement of the Reliability and Efficiency of Intelligent Electricity Inspection: IAOA-BP Algorithm for Anomaly Detection," Energies, MDPI, vol. 16(7), pages 1-15, March.
- Palaniappan, Somasundaram & Karuppannan, Sundararaju & Velusamy, Durgadevi, 2024. "Categorization of Indian residential consumers electrical energy consumption pattern using clustering and classification techniques," Energy, Elsevier, vol. 289(C).
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Keywords
Building energy consumption; Dynamic anomaly detection; Semi-supervised algorithm; Particle swarm optimization; K-medoids algorithm; KNN algorithm;All these keywords.
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