{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T16:33:08Z","timestamp":1776529988698,"version":"3.51.2"},"publisher-location":"New York, NY, USA","reference-count":17,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,9,17]],"date-time":"2021-09-17T00:00:00Z","timestamp":1631836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"SEED FUND URND"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,9,17]]},"DOI":"10.1145\/3490725.3490748","type":"proceedings-article","created":{"date-parts":[[2021,12,29]],"date-time":"2021-12-29T23:52:48Z","timestamp":1640821968000},"page":"151-156","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":24,"title":["Random Undersampling on Imbalance Time Series Data for Anomaly Detection"],"prefix":"10.1145","author":[{"given":"Mulyana","family":"Saripuddin","sequence":"first","affiliation":[{"name":"College of Computing and Informatics, Universiti Tenaga Nasional, Malaysia"}]},{"given":"Azizah","family":"Suliman","sequence":"additional","affiliation":[{"name":"College of Computing and Informatics, Universiti Tenaga Nasional, Malaysia"}]},{"given":"Sera","family":"Syarmila Sameon","sequence":"additional","affiliation":[{"name":"College of Computing and Informatics, Universiti Tenaga Nasional, Malaysia"}]},{"given":"Bo Norregaard","family":"Jorgensen","sequence":"additional","affiliation":[{"name":"Head of Center for Energy Informatics, University of Southern Denmark, Denmark"}]}],"member":"320","published-online":{"date-parts":[[2021,12,29]]},"reference":[{"key":"e_1_3_2_2_1_1","first-page":"2267","volume":"201","author":"Madasamy K.","unstructured":"Madasamy , K. and M. Ramaswami , Data imbalance and classifiers: impact and solutions from a big data perspective. International Journal of Computational Intelligence Research , 201 7. 13(9): p. 2267 - 2281 . Madasamy, K. and M. Ramaswami, Data imbalance and classifiers: impact and solutions from a big data perspective. International Journal of Computational Intelligence Research, 2017. 13(9): p. 2267-2281.","journal-title":"Computational Intelligence Research"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1142\/S0219622006002258"},{"key":"e_1_3_2_2_3_1","volume-title":"International Research Journal of Engineering and Technology (IRJET)","author":"Mishra S.","year":"2017","unstructured":"Mishra , S. , Handling imbalanced data: SMOTE vs. random undersampling . International Research Journal of Engineering and Technology (IRJET) , 2017 . 4(8). Mishra, S., Handling imbalanced data: SMOTE vs. random undersampling. International Research Journal of Engineering and Technology (IRJET), 2017. 4(8)."},{"key":"e_1_3_2_2_4_1","first-page":"429","volume":"202","author":"Thabtah F.","unstructured":"Thabtah , F. , , Data imbalance in classification: Experimental evaluation. Information Sciences , 202 0. 513: p. 429 - 441 . Thabtah, F., , Data imbalance in classification: Experimental evaluation. Information Sciences, 2020. 513: p. 429-441.","journal-title":"Information Sciences"},{"key":"e_1_3_2_2_5_1","first-page":"47","volume":"201","author":"Tsai C.","unstructured":"Tsai , C. - F. , , Under -sampling class imbalanced datasets by combining clustering analysis and instance selection. Information Sciences , 201 9. 477: p. 47 - 54 . Tsai, C.-F., , Under-sampling class imbalanced datasets by combining clustering analysis and instance selection. Information Sciences, 2019. 477: p. 47-54.","journal-title":"Information Sciences"},{"key":"e_1_3_2_2_6_1","first-page":"31","volume":"201","author":"Tao X.","unstructured":"Tao , X. , , Self-adaptive cost weights-based support vector machine cost-sensitive ensemble for imbalanced data classification. Information Sciences , 201 9. 487: p. 31 - 56 . Tao, X., , Self-adaptive cost weights-based support vector machine cost-sensitive ensemble for imbalanced data classification. Information Sciences, 2019. 487: p. 31-56.","journal-title":"Information Sciences"},{"key":"e_1_3_2_2_7_1","first-page":"3310","volume-title":"Energies","author":"Hasan M.","year":"2019","unstructured":"Hasan , M. , , Electricity theft detection in smart grid systems: a CNN-LSTM based approach . Energies , 2019 . 12(17): p. 3310 . Hasan, M., , Electricity theft detection in smart grid systems: a CNN-LSTM based approach. Energies, 2019. 12(17): p. 3310."},{"key":"e_1_3_2_2_8_1","volume-title":"Electricity Theft Detection in Power Grids with Deep Learning and Random Forests. Journal of Electrical and Computer Engineering","author":"Li S.","year":"2019","unstructured":"Li , S. , , Electricity Theft Detection in Power Grids with Deep Learning and Random Forests. Journal of Electrical and Computer Engineering , 2019 . 2019: p. 4136874. Li, S., , Electricity Theft Detection in Power Grids with Deep Learning and Random Forests. Journal of Electrical and Computer Engineering, 2019. 2019: p. 4136874."},{"key":"e_1_3_2_2_9_1","first-page":"8023","volume-title":"Sustainability","author":"Khan Z.A.","year":"2020","unstructured":"Khan , Z.A. , , Electricity theft detection using supervised learning techniques on smart meter data . Sustainability , 2020 . 12(19): p. 8023 . Khan, Z.A., , Electricity theft detection using supervised learning techniques on smart meter data. Sustainability, 2020. 12(19): p. 8023."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/IRI.2018.00018"},{"key":"e_1_3_2_2_11_1","first-page":"7171","volume":"201","author":"Avila N.F.","unstructured":"Avila , N.F. , G. Figueroa , and C. -C. Chu , NTL detection in electric distribution systems using the maximal overlap discrete wavelet-packet transform and random undersampling boosting. IEEE Transactions on Power Systems , 201 8. 33(6): p. 7171 - 7180 . Avila, N.F., G. Figueroa, and C.-C. Chu, NTL detection in electric distribution systems using the maximal overlap discrete wavelet-packet transform and random undersampling boosting. IEEE Transactions on Power Systems, 2018. 33(6): p. 7171-7180.","journal-title":"Power Systems"},{"key":"e_1_3_2_2_12_1","first-page":"161","volume":"201","author":"Moniz N.","unstructured":"Moniz , N. , P. Branco , and L. Torgo , Resampling strategies for imbalanced time series forecasting. International Journal of Data Science and Analytics , 201 7. 3(3): p. 161 - 181 . Moniz, N., P. Branco, and L. Torgo, Resampling strategies for imbalanced time series forecasting. International Journal of Data Science and Analytics, 2017. 3(3): p. 161-181.","journal-title":"Analytics"},{"key":"e_1_3_2_2_13_1","first-page":"2661","volume":"201","author":"Buzau M.M.","unstructured":"Buzau , M.M. , , Detection of non-technical losses using smart meter data and supervised learning. IEEE Transactions on Smart Grid , 201 8. 10(3): p. 2661 - 2670 . Buzau, M.M., , Detection of non-technical losses using smart meter data and supervised learning. IEEE Transactions on Smart Grid, 2018. 10(3): p. 2661-2670.","journal-title":"Smart Grid"},{"key":"e_1_3_2_2_14_1","first-page":"1606","volume":"201","author":"Zheng Z.","unstructured":"Zheng , Z. , , Wide and deep convolutional neural networks for electricity-theft detection to secure smart grids. IEEE Transactions on Industrial Informatics , 201 7. 14(4): p. 1606 - 1615 . Zheng, Z., , Wide and deep convolutional neural networks for electricity-theft detection to secure smart grids. IEEE Transactions on Industrial Informatics, 2017. 14(4): p. 1606-1615.","journal-title":"Industrial Informatics"},{"key":"e_1_3_2_2_15_1","volume-title":"Anomaly detection frameworks for identifying energy theft and meter irregularities in smart grids\/Yip Sook Chin","author":"Yip S.C.","year":"2019","unstructured":"Yip , S.C. , Anomaly detection frameworks for identifying energy theft and meter irregularities in smart grids\/Yip Sook Chin . 2019 , University of Malaya . Yip, S.C., Anomaly detection frameworks for identifying energy theft and meter irregularities in smart grids\/Yip Sook Chin. 2019, University of Malaya."},{"key":"e_1_3_2_2_16_1","volume":"202","author":"Saeed M.S.","unstructured":"Saeed , M.S. , , Detection of Non-Technical Losses in Power Utilities\u2014 A Comprehensive Systematic Review. 202 0. 13(18): p. 4727. Saeed, M.S., , Detection of Non-Technical Losses in Power Utilities\u2014A Comprehensive Systematic Review. 2020. 13(18): p. 4727.","journal-title":"Comprehensive Systematic Review."},{"key":"e_1_3_2_2_17_1","volume-title":"Electricity Theft Detection with self-attention. arXiv preprint arXiv:2002.06219","author":"Finardi P.","year":"2020","unstructured":"Finardi , P. , , Electricity Theft Detection with self-attention. arXiv preprint arXiv:2002.06219 , 2020 . Finardi, P., , Electricity Theft Detection with self-attention. arXiv preprint arXiv:2002.06219, 2020."}],"event":{"name":"MLMI'21: 2021 The 4th International Conference on Machine Learning and Machine Intelligence","location":"Hangzhou China","acronym":"MLMI'21"},"container-title":["2021 The 4th International Conference on Machine Learning and Machine Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3490725.3490748","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3490725.3490748","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:30:30Z","timestamp":1750188630000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3490725.3490748"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,17]]},"references-count":17,"alternative-id":["10.1145\/3490725.3490748","10.1145\/3490725"],"URL":"https:\/\/doi.org\/10.1145\/3490725.3490748","relation":{},"subject":[],"published":{"date-parts":[[2021,9,17]]},"assertion":[{"value":"2021-12-29","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}