Improved tri-training method for identifying user abnormal behavior based on adaptive golden jackal algorithm
Identification of abnormal user behavior helps reduce non-technical losses and regulatory operating costs for power marketing departments. Therefore, this paper proposes an adaptive golden jackal algorithm optimization improved tri-training method to identify user abnormal behavior. First, this pape...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2023-03-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0147299 |
| _version_ | 1797771905857486848 |
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| author | Kun Wang Jinggeng Gao Xiaohua Kang Huan Li |
| author_facet | Kun Wang Jinggeng Gao Xiaohua Kang Huan Li |
| author_sort | Kun Wang |
| collection | DOAJ |
| description | Identification of abnormal user behavior helps reduce non-technical losses and regulatory operating costs for power marketing departments. Therefore, this paper proposes an adaptive golden jackal algorithm optimization improved tri-training method to identify user abnormal behavior. First, this paper constructs multiple weak learners based on the abnormal behavior data of users, combined with the method of sampling and putting back, and uses the filtering method to select the tri-training base model. Second, aiming at the problem that the traditional optimization algorithm has a slow convergence speed and is easy to fall into local optimization, the adaptive golden jackal algorithm is used to realize the parameter optimization of tri-training. Based on the electricity consumption data of a certain place in the past five years, it is found that the model can provide stable identification results: accuracy = 0.987, f1-score = 0.973. |
| first_indexed | 2024-03-12T21:44:23Z |
| format | Article |
| id | doaj.art-7dd431ac49a54469a8687585c7aa830d |
| institution | Directory Open Access Journal |
| issn | 2158-3226 |
| language | English |
| last_indexed | 2024-03-12T21:44:23Z |
| publishDate | 2023-03-01 |
| publisher | AIP Publishing LLC |
| record_format | Article |
| series | AIP Advances |
| spelling | doaj.art-7dd431ac49a54469a8687585c7aa830d2023-07-26T14:03:57ZengAIP Publishing LLCAIP Advances2158-32262023-03-01133035030035030-710.1063/5.0147299Improved tri-training method for identifying user abnormal behavior based on adaptive golden jackal algorithmKun Wang0Jinggeng Gao1Xiaohua Kang2Huan Li3State Grid Gansu Electric Power Company Marketing Service Center, Lanzhou 730030, ChinaState Grid Gansu Electric Power Research Institute, Lanzhou 730030, ChinaState Grid Gansu Electric Power Research Institute, Lanzhou 730030, ChinaState Grid Gansu Electric Power Company Marketing Service Center, Lanzhou 730030, ChinaIdentification of abnormal user behavior helps reduce non-technical losses and regulatory operating costs for power marketing departments. Therefore, this paper proposes an adaptive golden jackal algorithm optimization improved tri-training method to identify user abnormal behavior. First, this paper constructs multiple weak learners based on the abnormal behavior data of users, combined with the method of sampling and putting back, and uses the filtering method to select the tri-training base model. Second, aiming at the problem that the traditional optimization algorithm has a slow convergence speed and is easy to fall into local optimization, the adaptive golden jackal algorithm is used to realize the parameter optimization of tri-training. Based on the electricity consumption data of a certain place in the past five years, it is found that the model can provide stable identification results: accuracy = 0.987, f1-score = 0.973.http://dx.doi.org/10.1063/5.0147299 |
| spellingShingle | Kun Wang Jinggeng Gao Xiaohua Kang Huan Li Improved tri-training method for identifying user abnormal behavior based on adaptive golden jackal algorithm AIP Advances |
| title | Improved tri-training method for identifying user abnormal behavior based on adaptive golden jackal algorithm |
| title_full | Improved tri-training method for identifying user abnormal behavior based on adaptive golden jackal algorithm |
| title_fullStr | Improved tri-training method for identifying user abnormal behavior based on adaptive golden jackal algorithm |
| title_full_unstemmed | Improved tri-training method for identifying user abnormal behavior based on adaptive golden jackal algorithm |
| title_short | Improved tri-training method for identifying user abnormal behavior based on adaptive golden jackal algorithm |
| title_sort | improved tri training method for identifying user abnormal behavior based on adaptive golden jackal algorithm |
| url | http://dx.doi.org/10.1063/5.0147299 |
| work_keys_str_mv | AT kunwang improvedtritrainingmethodforidentifyinguserabnormalbehaviorbasedonadaptivegoldenjackalalgorithm AT jinggenggao improvedtritrainingmethodforidentifyinguserabnormalbehaviorbasedonadaptivegoldenjackalalgorithm AT xiaohuakang improvedtritrainingmethodforidentifyinguserabnormalbehaviorbasedonadaptivegoldenjackalalgorithm AT huanli improvedtritrainingmethodforidentifyinguserabnormalbehaviorbasedonadaptivegoldenjackalalgorithm |