{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T13:11:00Z","timestamp":1780578660306,"version":"3.54.1"},"reference-count":50,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neural Networks"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.neunet.2026.109177","type":"journal-article","created":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T23:39:24Z","timestamp":1779838764000},"page":"109177","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["EDA-OCBLS: An error-distribution aware one-class broad learning system for anomaly detection"],"prefix":"10.1016","volume":"203","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5727-3697","authenticated-orcid":false,"given":"M.","family":"Tanveer","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A.","family":"Mishra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0516-316X","authenticated-orcid":false,"given":"A.","family":"Quadir","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-0465-5211","authenticated-orcid":false,"given":"M.","family":"Sajid","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.neunet.2026.109177_bib0001","series-title":"Data mining: The textbook","first-page":"265","article-title":"Outlier analysis: Advanced concepts","author":"Aggarwal","year":"2015"},{"issue":"1","key":"10.1016\/j.neunet.2026.109177_bib0002","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1109\/TNNLS.2017.2716952","article-title":"Broad learning system: An effective and efficient incremental learning system without the need for deep architecture","volume":"29","author":"Chen","year":"2017","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"10.1016\/j.neunet.2026.109177_bib0003","doi-asserted-by":"crossref","first-page":"196","DOI":"10.54254\/2753-8818\/38\/20240595","article-title":"The Gaussian distribution: Derivation method and its applications in selected examples","volume":"38","author":"Chen","year":"2024","journal-title":"Theoretical and Natural Science"},{"key":"10.1016\/j.neunet.2026.109177_bib0004","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.128533","article-title":"Double-kernel based bayesian approximation broad learning system with dropout","volume":"610","author":"Chen","year":"2024","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neunet.2026.109177_bib0005","first-page":"1","article-title":"Sparse bayesian broad learning system via adaptive lasso priors for robust regression","author":"Chen","year":"2025","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"10.1016\/j.neunet.2026.109177_bib0006","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.113803","article-title":"Minimum variance weighted broad cascade network structure for imbalanced classification","volume":"324","author":"Chen","year":"2025","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.neunet.2026.109177_bib0007","series-title":"Proceedings 2001 international conference on image processing (cat. no.01CH37205), volume 1","first-page":"34","article-title":"One-class SVM for learning in image retrieval","volume":"vol. 1","author":"Chen","year":"2001"},{"issue":"13","key":"10.1016\/j.neunet.2026.109177_bib0008","doi-asserted-by":"crossref","first-page":"1236","DOI":"10.1016\/j.patrec.2009.05.007","article-title":"Least squares one-class support vector machine","volume":"30","author":"Choi","year":"2009","journal-title":"Pattern Recognition Letters"},{"issue":"3","key":"10.1016\/j.neunet.2026.109177_bib0009","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1023\/A:1022627411411","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Machine Learning"},{"issue":"1","key":"10.1016\/j.neunet.2026.109177_bib0010","first-page":"1","article-title":"Statistical comparisons of classifiers over multiple data sets","volume":"7","author":"Dem\u0161ar","year":"2006","journal-title":"Journal of Machine Learning Research"},{"issue":"3","key":"10.1016\/j.neunet.2026.109177_bib0011","doi-asserted-by":"crossref","first-page":"2366","DOI":"10.1109\/TITS.2021.3088998","article-title":"Histogram-based intrusion detection and filtering framework for secure and safe in-vehicle networks","volume":"23","author":"Derhab","year":"2022","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"10.1016\/j.neunet.2026.109177_bib0012","unstructured":"Dua, D., Graff, C. et al. (2017). UCI machine learning repository, 7(1), 62. http:\/\/archive.ics.uci.edu\/ml."},{"key":"10.1016\/j.neunet.2026.109177_bib0013","series-title":"Deep learning","author":"Goodfellow","year":"2016"},{"key":"10.1016\/j.neunet.2026.109177_bib0014","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.121201","article-title":"Distance-based one-class time-series classification approach using local cluster balance","volume":"235","author":"Hayashi","year":"2024","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.neunet.2026.109177_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.128638","article-title":"Double kernel and minimum variance embedded broad learning system based autoencoder for one-class classification","volume":"611","author":"He","year":"2025","journal-title":"Neurocomputing"},{"issue":"3","key":"10.1016\/j.neunet.2026.109177_bib0016","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1017\/S0890060419000155","article-title":"One-class support vector machines with a bias constraint and its application in system reliability prediction","volume":"33","author":"Hu","year":"2019","journal-title":"Artificial Intelligence for Engineering Design, Analysis and Manufacturing"},{"issue":"11","key":"10.1016\/j.neunet.2026.109177_bib0017","doi-asserted-by":"crossref","first-page":"16076","DOI":"10.1109\/TNNLS.2023.3291793","article-title":"Flexible label-induced manifold broad learning system for multiclass recognition","volume":"35","author":"Jin","year":"2024","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"10","key":"10.1016\/j.neunet.2026.109177_bib0018","doi-asserted-by":"crossref","first-page":"4959","DOI":"10.1109\/TKDE.2021.3049540","article-title":"Pattern classification with corrupted labeling via robust broad learning system","volume":"34","author":"Jin","year":"2022","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"3","key":"10.1016\/j.neunet.2026.109177_bib0019","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1017\/S026988891300043X","article-title":"One-class classification: Taxonomy of study and review of techniques","volume":"29","author":"Khan","year":"2014","journal-title":"The Knowledge Engineering Review"},{"key":"10.1016\/j.neunet.2026.109177_bib0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.108240","article-title":"Shallow and ensemble deep randomized neural network for anomaly detection","volume":"195","author":"Kumari","year":"2026","journal-title":"Neural Networks"},{"issue":"1","key":"10.1016\/j.neunet.2026.109177_bib0021","article-title":"One-class classification with extreme learning machine","volume":"2015","author":"Leng","year":"2015","journal-title":"Mathematical Problems in Engineering"},{"key":"10.1016\/j.neunet.2026.109177_bib0022","series-title":"Proceedings of the 14th ACM international conference on web search and data mining","first-page":"1127","article-title":"Deep learning for anomaly detection: Challenges, methods, and opportunities","author":"Pang","year":"2021"},{"issue":"2","key":"10.1016\/j.neunet.2026.109177_bib0023","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/0925-2312(94)90053-1","article-title":"Learning and generalization characteristics of the random vector functional-link net","volume":"6","author":"Pao","year":"1994","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neunet.2026.109177_bib0024","series-title":"International conference on neural information processing","first-page":"244","article-title":"One class restricted kernel machines","author":"Quadir","year":"2024"},{"issue":"12","key":"10.1016\/j.neunet.2026.109177_bib0025","first-page":"1848","article-title":"A detailed analysis on NSL-KDD dataset using various machine learning techniques for intrusion detection","volume":"2","author":"Revathi","year":"2013","journal-title":"International Journal of Engineering Research & Technology (IJERT)"},{"key":"10.1016\/j.neunet.2026.109177_bib0026","series-title":"Proceedings of the 35th international conference on machine learning","first-page":"4393","article-title":"Deep one-class classification","volume":"vol. 80","author":"Ruff","year":"2018"},{"issue":"6088","key":"10.1016\/j.neunet.2026.109177_bib0027","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1038\/323533a0","article-title":"Learning representations by back-propagating errors","volume":"323","author":"Rumelhart","year":"1986","journal-title":"Nature"},{"issue":"8","key":"10.1016\/j.neunet.2026.109177_bib0028","doi-asserted-by":"crossref","first-page":"4460","DOI":"10.1109\/TFUZZ.2024.3400898","article-title":"Intuitionistic fuzzy broad learning system: Enhancing robustness against noise and outliers","volume":"32","author":"Sajid","year":"2024","journal-title":"IEEE Transactions on Fuzzy Systems"},{"issue":"5","key":"10.1016\/j.neunet.2026.109177_bib0029","doi-asserted-by":"crossref","first-page":"2738","DOI":"10.1109\/TFUZZ.2024.3359652","article-title":"Neuro-fuzzy random vector functional link neural network for classification and regression problems","volume":"32","author":"Sajid","year":"2024","journal-title":"IEEE Transactions on Fuzzy Systems"},{"issue":"3","key":"10.1016\/j.neunet.2026.109177_bib0030","first-page":"829","article-title":"A comprehensive survey of anomaly detection algorithms","volume":"10","author":"Samariya","year":"2023","journal-title":"Annals of Data Science"},{"key":"10.1016\/j.neunet.2026.109177_bib0031","series-title":"Advances in neural information processing systems","article-title":"Support vector method for novelty detection","volume":"vol. 12","author":"Sch\u00f6lkopf","year":"1999"},{"key":"10.1016\/j.neunet.2026.109177_bib0032","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.108999","article-title":"Graph-embedded subspace support vector data description","volume":"133","author":"Sohrab","year":"2023","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.neunet.2026.109177_bib0033","series-title":"2018 24th international conference on pattern recognition (ICPR)","first-page":"722","article-title":"Subspace support vector data description","author":"Sohrab","year":"2018"},{"key":"10.1016\/j.neunet.2026.109177_bib0034","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2020.107648","article-title":"Multimodal subspace support vector data description","volume":"110","author":"Sohrab","year":"2021","journal-title":"Pattern Recognition"},{"issue":"4","key":"10.1016\/j.neunet.2026.109177_bib0035","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1109\/TNNLS.2015.2424995","article-title":"Extreme learning machine for multilayer perceptron","volume":"27","author":"Tang","year":"2016","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"10.1016\/j.neunet.2026.109177_bib0036","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.112940","article-title":"BLS-CIL: Class imbalance broad learning system via dual weighting and layer trimming","volume":"174","author":"Tanveer","year":"2026","journal-title":"Pattern Recognition"},{"issue":"11","key":"10.1016\/j.neunet.2026.109177_bib0037","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.1016\/S0167-8655(99)00087-2","article-title":"Support vector domain description","volume":"20","author":"Tax","year":"1999","journal-title":"Pattern Recognition Letters"},{"key":"10.1016\/j.neunet.2026.109177_bib0038","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1023\/B:MACH.0000008084.60811.49","article-title":"Support vector data description","volume":"54","author":"Tax","year":"2004","journal-title":"Machine Learning"},{"key":"10.1016\/j.neunet.2026.109177_bib0039","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.126389","article-title":"Mixture-of-experts-based broad learning system and its applications","volume":"269","author":"Wang","year":"2025","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.neunet.2026.109177_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.108032","article-title":"Broad learning system via adaptive maximum weighted correntropy","volume":"193","author":"Wang","year":"2026","journal-title":"Neural Networks"},{"issue":"7","key":"10.1016\/j.neunet.2026.109177_bib0041","first-page":"2609","article-title":"A deep one-class neural network for anomalous event detection in complex scenes","volume":"31","author":"Wu","year":"2020","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"10.1016\/j.neunet.2026.109177_bib0042","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.patcog.2018.07.015","article-title":"Robust one-class support vector machine with rescaled hinge loss function","volume":"84","author":"Xing","year":"2018","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.neunet.2026.109177_bib0043","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2020.107685","article-title":"Robust sparse coding for one-class classification based on correntropy and logarithmic penalty function","volume":"111","author":"Xing","year":"2021","journal-title":"Pattern Recognition"},{"issue":"11","key":"10.1016\/j.neunet.2026.109177_bib0044","doi-asserted-by":"crossref","first-page":"5723","DOI":"10.1109\/TKDE.2024.3393996","article-title":"Calibrated one-class classification for unsupervised time series anomaly detection","volume":"36","author":"Xu","year":"2024","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"1","key":"10.1016\/j.neunet.2026.109177_bib0045","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1109\/TII.2022.3157727","article-title":"Stacked one-class broad learning system for intrusion detection in industry 4.0","volume":"19","author":"Yang","year":"2023","journal-title":"IEEE Transactions on Industrial Informatics"},{"key":"10.1016\/j.neunet.2026.109177_bib0046","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.107468","article-title":"Broad learning system based on fractional order optimization","volume":"188","author":"Zhang","year":"2025","journal-title":"Neural Networks"},{"key":"10.1016\/j.neunet.2026.109177_bib0047","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106436","article-title":"Self-balancing incremental broad learning system with privacy protection","volume":"178","author":"Zhang","year":"2024","journal-title":"Neural Networks"},{"key":"10.1016\/j.neunet.2026.109177_bib0048","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.patrec.2021.04.020","article-title":"Anomaly detection using improved deep SVDD model with data structure preservation","volume":"148","author":"Zhang","year":"2021","journal-title":"Pattern Recognition Letters"},{"key":"10.1016\/j.neunet.2026.109177_bib0049","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106521","article-title":"Broad learning system based on maximum multi-kernel correntropy criterion","volume":"179","author":"Zhao","year":"2024","journal-title":"Neural Networks"},{"key":"10.1016\/j.neunet.2026.109177_bib0050","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2023.126324","article-title":"Multikernel correntropy based robust least squares one-class support vector machine","volume":"545","author":"Zheng","year":"2023","journal-title":"Neurocomputing"}],"container-title":["Neural Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026006386?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026006386?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T12:34:04Z","timestamp":1780576444000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0893608026006386"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":50,"alternative-id":["S0893608026006386"],"URL":"https:\/\/doi.org\/10.1016\/j.neunet.2026.109177","relation":{},"ISSN":["0893-6080"],"issn-type":[{"value":"0893-6080","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"EDA-OCBLS: An error-distribution aware one-class broad learning system for anomaly detection","name":"articletitle","label":"Article Title"},{"value":"Neural Networks","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neunet.2026.109177","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"109177"}}