{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T04:44:42Z","timestamp":1777697082503,"version":"3.51.4"},"reference-count":39,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62172457"],"award-info":[{"award-number":["62172457"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Research Project of Henan Province","award":["242102210104, 252102210032"],"award-info":[{"award-number":["242102210104, 252102210032"]}]},{"name":"Key Scientific Research Project of Higher Education Institutions of Henan Province, China","award":["25B520021"],"award-info":[{"award-number":["25B520021"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Intelligent Decision Technologies"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:p>Aiming at the problem of violent fluctuations caused by sudden abnormalities in power load forecasting due to extreme weather, equipment failure and other reasons, this paper introduces the Informer model to model sudden abnormal behaviors and uses Generative Adversarial Network (GAN) for intelligent error prevention. The GAN discriminator identifies and marks abnormal points, and the generator repairs abnormal data. Comparative experiments are conducted to verify the sudden anomaly recognition and repair capabilities of the intelligent error prevention mechanism in this paper. The ROC curve results show that the AUC value of the anomaly recognition designed in this paper is 0.95, significantly higher than 0.48 of the baseline model and 0.87 of the GAN model. In most cases, the load of the power system studied in this paper can respond in a shorter time, providing an efficient and intelligent solution for the power system to deal with emergencies. This enhances power load forecasting accuracy and system stability, offering new perspectives for intelligent error prevention and anomaly management in the power industry.<\/jats:p>","DOI":"10.1177\/18724981251390977","type":"journal-article","created":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T17:28:43Z","timestamp":1763659723000},"page":"3613-3627","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Abnormal behavior modeling and intelligent error prevention algorithm in AI load forecasting"],"prefix":"10.1177","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5059-7808","authenticated-orcid":false,"given":"Shaohui","family":"Zhang","sequence":"first","affiliation":[{"name":"Zhoukou Normal University"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-3894-8376","authenticated-orcid":false,"given":"Qiuying","family":"Han","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Zhoukou Normal University, Zhoukou, Henan, China"}]}],"member":"179","published-online":{"date-parts":[[2025,11,20]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-021-03444-x"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00202-021-01376-5"},{"key":"e_1_3_2_4_2","first-page":"2806","article-title":"Challenges and prospects for constructing the new-type power system towards a carbon neutrality future","volume":"42","author":"Zhang Z","year":"2022","unstructured":"Zhang Z, Kang C. Challenges and prospects for constructing the new-type power system towards a carbon neutrality future. Proc CSEE 2022; 42: 2806\u20132818.","journal-title":"Proc CSEE"},{"key":"e_1_3_2_5_2","first-page":"1741","article-title":"Primary exploration of six essential factors in new power system","volume":"47","author":"Kang C","year":"2023","unstructured":"Kang C, Du E, Guo H, et\u00a0al. Primary exploration of six essential factors in new power system. Power Syst Technol 2023; 47: 1741\u20131750.","journal-title":"Power Syst Technol"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2021.06.009"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.14716\/ijtech.v13i6.5931"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.3233\/JIFS-235218"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2021.120109"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2023.118997"},{"key":"e_1_3_2_11_2","unstructured":"Panagoulias DP Sarmas E Marinakis V et\u00a0al. Integrating dynamic correlation shifts and weighted benchmarking in extreme value analysis. arXiv preprint arXiv:2411 13608. 2024."},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2022.3168529"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1049\/gtd2.13273"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-023-01160-4"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-022-10199-0"},{"key":"e_1_3_2_16_2","first-page":"767","article-title":"Comparison of missing data imputation methods in time series forecasting","volume":"70","author":"Ahn H","year":"2022","unstructured":"Ahn H, Sun K, Kim KP. Comparison of missing data imputation methods in time series forecasting. Comput Mater Contin 2022; 70: 767\u2013779.","journal-title":"Comput Mater Contin"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-024-05575-y"},{"key":"e_1_3_2_18_2","first-page":"141","article-title":"Advanced stock price prediction using LSTM and informer models","volume":"5","author":"Duan C","year":"2024","unstructured":"Duan C, Ke W. Advanced stock price prediction using LSTM and informer models. J\u00a0Artif Intell Gen Sci (JAIGS) ISSN: 3006-4023 2024; 5: 141\u2013166.","journal-title":"J\u00a0Artif Intell Gen Sci (JAIGS) ISSN: 3006-4023"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3152247"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-023-10595-0"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-022-01676-7"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-023-08687-7"},{"key":"e_1_3_2_23_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3637061","article-title":"On the effectiveness of sampled softmax loss for item recommendation","volume":"42","author":"Wu J","year":"2024","unstructured":"Wu J, Wang X, Gao X, et\u00a0al. On the effectiveness of sampled softmax loss for item recommendation. ACM Trans Inf Syst 2024; 42: 1\u201326.","journal-title":"ACM Trans Inf Syst"},{"key":"e_1_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2022.3218590"},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPEL.2023.3266365"},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.1109\/TED.2023.3346369"},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.1109\/JLT.2023.3241188"},{"key":"e_1_3_2_28_2","first-page":"87","article-title":"Neural network synthesis of an optimal linear stochastic system according to the criterion of minimum mean square error","volume":"34","author":"Sinitsyn IN","year":"2024","unstructured":"Sinitsyn IN, Sinitsyn VI, Korepanov \u00c8RF, et\u00a0al. Neural network synthesis of an optimal linear stochastic system according to the criterion of minimum mean square error. Sist Sredstva Inform [Syst Means Inform] 2024; 34: 87\u2013108.","journal-title":"Sist Sredstva Inform [Syst Means Inform]"},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1137\/21M1437457"},{"key":"e_1_3_2_30_2","doi-asserted-by":"publisher","DOI":"10.1111\/biom.13505"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10511-022-09732-4"},{"key":"e_1_3_2_32_2","doi-asserted-by":"publisher","DOI":"10.30650\/jse.v3i2.3868"},{"key":"e_1_3_2_33_2","first-page":"1","article-title":"Modeling GDP using autoregressive integrated moving average (ARIMA) model: a systematic review","volume":"9","author":"Muma B","year":"2022","unstructured":"Muma B, Karoki A. Modeling GDP using autoregressive integrated moving average (ARIMA) model: a systematic review. Open Access Lib J 2022; 9: 1\u20138.","journal-title":"Open Access Lib J"},{"key":"e_1_3_2_34_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.aej.2022.01.011"},{"key":"e_1_3_2_35_2","doi-asserted-by":"publisher","DOI":"10.1002\/int.22620"},{"key":"e_1_3_2_36_2","doi-asserted-by":"publisher","DOI":"10.5194\/hess-28-4187-2024"},{"key":"e_1_3_2_37_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-021-05842-w"},{"key":"e_1_3_2_38_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10346-022-01923-6"},{"key":"e_1_3_2_39_2","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3169465"},{"key":"e_1_3_2_40_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11440-022-01495-8"}],"container-title":["Intelligent Decision Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/18724981251390977","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/18724981251390977","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/18724981251390977","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:21:50Z","timestamp":1777454510000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/18724981251390977"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11]]},"references-count":39,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025,11]]}},"alternative-id":["10.1177\/18724981251390977"],"URL":"https:\/\/doi.org\/10.1177\/18724981251390977","relation":{},"ISSN":["1872-4981","1875-8843"],"issn-type":[{"value":"1872-4981","type":"print"},{"value":"1875-8843","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11]]}}}