A novel energy-based online sequential extreme learning machine to detect anomalies over real-time data streams
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-021-05731-2.pdf
Reference45 articles.
1. Sample C, Schaffer K (2013) An overview of anomaly detection. IT Prof 15(1):8–11
2. Callegari C, Giordano S, Pagano M (2017) Anomaly detection: an overview of selected methods. In: 2017 international multi-conference on engineering, computer and information sciences (SIBIRCON), Novosibirsk, 2017, pp 52–57
3. Bhuyan MH, Bhattacharyya DK, Kalita JK (2014) Network anomaly detection: methods, systems and tools. In: IEEE communications surveys & tutorials, vol. 16, no. 1, pp 303–336, First Quarter
4. Rana AI, Estrada G, Solé M, Muntés V (2016) Anomaly detection guidelines for data streams in big data. In: 2016 3rd international conference on soft computing & machine intelligence (ISCMI), Dubai, 2016, pp 94–98
5. Rettig L, Khayati M, Cudré-Mauroux P, Piórkowski M (2015) Online anomaly detection over Big Data streams. In: 2015 IEEE international conference on big data (Big Data), Santa Clara, CA, 2015, pp 1113–1122
Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Analysis of Extreme Learning Machines (ELMs) for intelligent intrusion detection systems: A survey;Expert Systems with Applications;2024-11
2. Network intrusion detection: An optimized deep learning approach using big data analytics;Expert Systems with Applications;2024-10
3. Maximizing intrusion detection efficiency for IoT networks using extreme learning machine;Discover Internet of Things;2024-07-09
4. Incremental and sequence learning algorithms for weighted regularized extreme learning machines;Applied Intelligence;2024-04
5. Wavelet-based temporal models of human activity for anomaly detection in smart robot-assisted environments1;Journal of Ambient Intelligence and Smart Environments;2023-11-03
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3