Research on abnormal detection of daily loss rate based on a variational auto-encoder

ZHANG Guofang; LIU Tongyu; WEN Lili; GUO Guo; ZHOU Zhongxin; YUAN Peisen

doi:10.3969/j.issn.1000-5641.202091013

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Sep. 2020

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Article Navigation > Journal of East China Normal University (Natural Sciences) > 2020 > (5): 146-155

ZHANG Guofang, LIU Tongyu, WEN Lili, GUO Guo, ZHOU Zhongxin, YUAN Peisen. Research on abnormal detection of daily loss rate based on a variational auto-encoder[J]. Journal of East China Normal University (Natural Sciences), 2020, (5): 146-155. doi: 10.3969/j.issn.1000-5641.202091013

Citation:

ZHANG Guofang, LIU Tongyu, WEN Lili, GUO Guo, ZHOU Zhongxin, YUAN Peisen. Research on abnormal detection of daily loss rate based on a variational auto-encoder[J]. Journal of East China Normal University (Natural Sciences), 2020, (5): 146-155. doi: 10.3969/j.issn.1000-5641.202091013

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Research on abnormal detection of daily loss rate based on a variational auto-encoder

doi: 10.3969/j.issn.1000-5641.202091013

1.
State Grid Sichuan Electric Power Company, Chengdu　610041, China
2.
College of Information Science and Technology, Nanjing Agricultural University, Nanjing　210095, China
3.
NARI Technology Co. Ltd., Nanjing　211106, China

Received Date: 2020-08-14
Available Online: 2020-09-24
Publish Date: 2020-09-24

Abstract

Abstract

This paper adopts an anomaly detection algorithm based on a self-encoder to achieve anomaly detection of large-scale daily line loss rate data. A variational auto-encoder is a neural network that uses the backpropagation algorithm to make the output value approximately equal to the input value. It uses the auto-encoder to encode the original daily line loss rate time series and records the reconstruction possibility at each time point during the reconstruction process. When the reconstruction possibility is greater than a specified threshold, it is classified as anomaly data. In this paper, experiments were conducted on real daily line loss data. The test results show that the proposed algorithm for abnormal detection of daily line loss rate data based on an auto-encoder has good detection capability.
- auto-encoder,
- anomaly detection,
- daily line loss rate

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References(29)

References

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