{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T13:22:13Z","timestamp":1771248133976,"version":"3.50.1"},"reference-count":18,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T00:00:00Z","timestamp":1744156800000},"content-version":"vor","delay-in-days":98,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Intelligent Networks"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1016\/j.ijin.2025.04.002","type":"journal-article","created":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T12:23:16Z","timestamp":1744201396000},"page":"27-35","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Online and offline collaborative abnormal traffic intelligent detection system based on elastic lightweight width learning algorithm"],"prefix":"10.1016","volume":"6","author":[{"given":"Yu","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.ijin.2025.04.002_bib1","doi-asserted-by":"crossref","first-page":"1170","DOI":"10.2991\/ijcis.d.210301.003","article-title":"Abnormal traffic detection based on generative adversarial network and feature optimization selection","volume":"14","author":"Ma","year":"2021","journal-title":"Int. J. Comput. Intell. Syst."},{"issue":"1","key":"10.1016\/j.ijin.2025.04.002_bib2","first-page":"14131","article-title":"Random forests for detecting weak signals and extracting physical information: a case study of magnetic navigation","volume":"2","author":"Moradi","year":"2024","journal-title":"arxiv preprint arxiv:2402"},{"issue":"6","key":"10.1016\/j.ijin.2025.04.002_bib3","doi-asserted-by":"crossref","first-page":"1983","DOI":"10.1016\/j.asr.2023.05.044","article-title":"Improved real-time cycle-slip detection for Low Earth Orbit satellites based on the dynamic force model","volume":"72","author":"Gao","year":"2023","journal-title":"Adv. Space Res."},{"issue":"3","key":"10.1016\/j.ijin.2025.04.002_bib4","doi-asserted-by":"crossref","first-page":"1463","DOI":"10.1109\/TCYB.2020.2988792","article-title":"GreenSea: visual soccer analysis using broad learning system","volume":"51","author":"Sheng","year":"2020","journal-title":"IEEE Trans. Cybern."},{"issue":"4","key":"10.1016\/j.ijin.2025.04.002_bib5","doi-asserted-by":"crossref","first-page":"4197","DOI":"10.1109\/TNSM.2021.3120804","article-title":"Network abnormal traffic detection model based on semi-supervised deep reinforcement learning","volume":"18","author":"Dong","year":"2021","journal-title":"IEEE Transactions on Network and Service Management"},{"issue":"1","key":"10.1016\/j.ijin.2025.04.002_bib6","doi-asserted-by":"crossref","first-page":"1201","DOI":"10.1080\/09540091.2022.2051434","article-title":"The abnormal traffic detection scheme based on PCA and SSH","volume":"34","author":"Wang","year":"2022","journal-title":"Connect. Sci."},{"issue":"3","key":"10.1016\/j.ijin.2025.04.002_bib7","doi-asserted-by":"crossref","first-page":"3743","DOI":"10.1002\/ett.3743","article-title":"A machine learning based framework for IoT device identification and abnormal traffic detection","volume":"33","author":"Salman","year":"2022","journal-title":"Transactions on Emerging Telecommunications Technologies"},{"issue":"2","key":"10.1016\/j.ijin.2025.04.002_bib8","doi-asserted-by":"crossref","first-page":"410","DOI":"10.3390\/s22020410","article-title":"An efficient multilevel probabilistic model for abnormal traffic detection in wireless sensor networks","volume":"22","author":"Khan","year":"2022","journal-title":"Sensors"},{"issue":"1","key":"10.1016\/j.ijin.2025.04.002_bib9","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1109\/TSMC.2020.2995205","article-title":"Analysis and variants of broad learning system","volume":"52","author":"Zhang","year":"2020","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics: Systems"},{"issue":"3","key":"10.1016\/j.ijin.2025.04.002_bib10","first-page":"983","article-title":"Semi-supervised broad learning system based on manifold regularization and broad network","volume":"67","author":"Zhao","year":"2020","journal-title":"IEEE Transactions on Circuits and Systems I: Regular Papers"},{"issue":"11","key":"10.1016\/j.ijin.2025.04.002_bib11","doi-asserted-by":"crossref","first-page":"6983","DOI":"10.1109\/TNNLS.2021.3081568","article-title":"Frequency principle in broad learning system","volume":"33","author":"Chen","year":"2021","journal-title":"IEEE Transact. Neural Networks Learn. Syst."},{"issue":"9","key":"10.1016\/j.ijin.2025.04.002_bib12","doi-asserted-by":"crossref","first-page":"4450","DOI":"10.1109\/TCYB.2020.2978500","article-title":"Adaptive deep cascade broad learning system and its application in image denoising","volume":"51","author":"Ye","year":"2020","journal-title":"IEEE Trans. Cybern."},{"issue":"5","key":"10.1016\/j.ijin.2025.04.002_bib13","doi-asserted-by":"crossref","first-page":"896","DOI":"10.1016\/j.icte.2022.11.006","article-title":"A-CAVE: network abnormal traffic detection algorithm based on variational autoencoder","volume":"9","author":"Su","year":"2023","journal-title":"ICT Express"},{"issue":"6","key":"10.1016\/j.ijin.2025.04.002_bib14","doi-asserted-by":"crossref","first-page":"2596","DOI":"10.1007\/s11036-022-02075-6","article-title":"A GAN-based intrusion detection model for 5G enabled future metaverse","volume":"27","author":"Ding","year":"2022","journal-title":"Mobile Network. Appl."},{"issue":"3","key":"10.1016\/j.ijin.2025.04.002_bib15","first-page":"170","article-title":"Machine learning methodology for identifying vehicles using image processing","volume":"1","author":"Hasanvand","year":"2023","journal-title":"AIA"},{"issue":"22","key":"10.1016\/j.ijin.2025.04.002_bib16","doi-asserted-by":"crossref","first-page":"11752","DOI":"10.3390\/app122211752","article-title":"A study of network intrusion detection systems using artificial intelligence\/machine learning","volume":"12","author":"Vanin","year":"2022","journal-title":"Appl. Sci."},{"issue":"1","key":"10.1016\/j.ijin.2025.04.002_bib17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13677-022-00361-y","article-title":"NIDD: an intelligent network intrusion detection model for nursing homes","volume":"11","author":"Zhou","year":"2022","journal-title":"J. Cloud Comput."},{"issue":"3","key":"10.1016\/j.ijin.2025.04.002_bib18","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1007\/s13177-023-00362-4","article-title":"Intelligent traffic prediction by combining weather and road traffic condition information: a deep learning-based approach","volume":"21","author":"Kar","year":"2023","journal-title":"International journal of intelligent transportation systems research"}],"container-title":["International Journal of Intelligent Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2666603025000053?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2666603025000053?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T12:39:14Z","timestamp":1771245554000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2666603025000053"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":18,"alternative-id":["S2666603025000053"],"URL":"https:\/\/doi.org\/10.1016\/j.ijin.2025.04.002","relation":{},"ISSN":["2666-6030"],"issn-type":[{"value":"2666-6030","type":"print"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Online and offline collaborative abnormal traffic intelligent detection system based on elastic lightweight width learning algorithm","name":"articletitle","label":"Article Title"},{"value":"International Journal of Intelligent Networks","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ijin.2025.04.002","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.","name":"copyright","label":"Copyright"}]}}