Abstract
It is of great significance for the power supply enterprise to analyze the electrical power consumption data. However, there is no effective way to separate abnormal data. This paper presents a classification method for high dimensional power consumption data classification. Based on the information theory, the proposed method consists of two parts, feature selecting and classification of selected features by logistic regression. The experimental results below show that the method has a lower computational complexity than that of data classification without pretreatment, and higher efficiency and reliability than random feature selection.
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Li, C., Zu, Y., Hou, B. (2016). A Feature Selection Method of Power Consumption Data. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2016. ICCSA 2016. Lecture Notes in Computer Science(), vol 9786. Springer, Cham. https://doi.org/10.1007/978-3-319-42085-1_44
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DOI: https://doi.org/10.1007/978-3-319-42085-1_44
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