Open Access
| Issue |
E3S Web Conf.
Volume 257, 2021
5th International Workshop on Advances in Energy Science and Environment Engineering (AESEE 2021)
|
|
|---|---|---|
| Article Number | 02060 | |
| Number of page(s) | 6 | |
| Section | Research on Energy Consumption and Energy Industry Benefit | |
| DOI | https://doi.org/10.1051/e3sconf/202125702060 | |
| Published online | 12 May 2021 | |
- Seem, J.E. (2007) Using intelligent data analysis to detect abnormal energy consumption in buildings. J. Using intelligent data analysis to detect abnormal energy consumption in buildings. Energy. &. Buildings, 39(1): 52-58. [Google Scholar]
- Lin, G., Claridge, D.E. (2015) A temperature-based approach to detect abnormal building energy consumption. J. A temperature-based approach to detect abnormal building energy consumption. Jnergy. &. Buildings, 93: 110-118. [Google Scholar]
- Qing, X.X., Xiao, D., Wang, B. (2012) Data mining method for real-time monitoring of energy consumption. J. Data mining method for real-time monitoring of energy consumption. Journal. Of. Chongqing. University, 35(07): 133-137. [Google Scholar]
- Cabrera, D.F.M., Zareipour, H. (2013) Data association mining for identifying lighting energy waste patterns in educational institutes. J. Energy. &. Buildings, 62(Jul.): 210-216. [Google Scholar]
- Shi, D.L., Liu, J.Y., Li, K.N., et al. (2020) Fault diagnosis of chiller based on association rule classification. J. Fault diagnosis of chiller based on association rule classification. Journal. Of. Chiller. Engineering, 41(5): 66-75. [Google Scholar]
- Li, G.N., Hu, Y.P., Chen, H.X., et al. (2017) Data partitioning and association mining for identifying VRF energy consumption patterns under various part loads and refrigerant charge conditions. J. Data partitioning and association mining for identifying VRF energy consumption patterns under various part loads and refrigerant charge conditions. Applied. Energy, 39(1): 846-861. [Google Scholar]
- Wan, X., Hu, N.S., Han, P.F., et al. (2016) Research on the application of big data mining technology to the operation performance optimization of steam turbine. J. Research on the application of big data mining technology to the operation performance optimization of steam turbine. Jhinese. Journal. Of. Electrical. Engineering, 36(2): 459-467603. [Google Scholar]
- Chen, Y., Li, S.N., Zhang, L., et al. (2019) Defect correlation analysis of secondary equipment in Smart Substation Based on improved Apriori algorithm. J. Defect correlation analysis of secondary equipment in Smart Substation Based on improved Apriori algorithm. Protection. And. Control. Of. Power. System, 47(20): 135-141. [Google Scholar]
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