يعرض 1 - 10 نتائج من 32 نتيجة بحث عن '"self-organizing map algorithm"', وقت الاستعلام: 0.99s تنقيح النتائج
  1. 1
    دورية أكاديمية
    Minority Resampling Boosted Unsupervised Learning With Hyperdimensional Computing for Threat Detection at the Edge of Internet of Things

    المؤلفون: Christopher, V., Aathman, T., Mahendrakumaran, K., Nawaratne, R., De Silva, D., Nanayakkara, V., Alahakoon, D.

    المصدر: IEEE Access Access, IEEE. 9:126646-126657 2021

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  2. 2
    دورية أكاديمية
    Adaptive cross-site scripting attack detection framework for smart devices security using intelligent filters and attack ontology

    المؤلفون: Chaudhary, Pooja, Gupta, B. B.Aff2, Aff3, Aff4, Aff5, IDs00500022076972_cor2, Singh, A. K.

    المصدر: Soft Computing: A Fusion of Foundations, Methodologies and Applications. 27(8):4593-4608

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  3. 3
    مؤتمر
    A new outlier detection base on the self-organizing map algorithm

    المؤلفون: Feng, Xiangdong, Li, Yueshan, Ma, Zhiyuan

    المصدر: Proceedings of the 32nd Chinese Control Conference Control Conference (CCC), 2013 32nd Chinese. :3944-3949 Jul, 2013

    Relation: 2013 32nd Chinese Control Conference (CCC)

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  4. 4
    دورية أكاديمية
    Minority Resampling Boosted Unsupervised Learning With Hyperdimensional Computing for Threat Detection at the Edge of Internet of Things

    المؤلفون: Vivek Christopher, Tharmasanthiran Aathman, Kayathiri Mahendrakumaran, Rashmika Nawaratne, Daswin De Silva, Vishaka Nanayakkara, Damminda Alahakoon

    المصدر: IEEE Access, Vol 9, Pp 126646-126657 (2021)

    مصطلحات موضوعية: Edge computing, cybersecurity, edge IoT, hyperdimensional computing, minority resampling unsupervised machine learning, growing self organizing map algorithm, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

    وصف الملف: electronic resource

    Relation: https://ieeexplore.ieee.org/document/9530655/; https://doaj.org/toc/2169-3536

    URL الوصول: https://doaj.org/article/92dba4f3ffbc49debd5a6d65570f7657

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  5. 5
    كتاب إلكتروني
    Adapting Self-Organizing Map Algorithm to Sparse Data

    المؤلفون: Melka, JosuéAff6, Mariage, Jean-JacquesAff6

    المساهمون: Kacprzyk, Janusz, Series EditorAff1, Sabourin, Christophe, editorAff2, Merelo, Juan Julian, editorAff3, Madani, Kurosh, editorAff4, Warwick, Kevin, editorAff5

    المصدر: Computational Intelligence : 9th International Joint Conference, IJCCI 2017 Funchal-Madeira, Portugal, November 1-3, 2017 Revised Selected Papers. 829:139-161

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  6. 6
    دورية أكاديمية
    High genetic differentiation of grapevine rootstock varieties determined by molecular markers and artificial neural networks

    المؤلفون: Costa, Marcia Oliveira, Capel, Livia Santos, Maldonado, Carlos, Mora, Freddy, Mangolin, Claudete Aparecida, Machado, Maria de Fátima Pires da Silva

    المصدر: Acta Scientiarum. Agronomy. January 2020 42

    مصطلحات موضوعية: clustering methods, RAPD-SSR loci, self-organizing map algorithm

    وصف الملف: text/html

    URL الوصول: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-86212020000102005

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  7. 7
    مؤتمر
    ART neural network based clustering method produces best quality clusters of fingerprints in comparison to Self Organizing Map and K-Means Clustering Algorithms

    المؤلفون: Gour, Bhupesh, Bandopadhyaya, T. K., Sharma, Sudhir

    المصدر: 2008 International Conference on Innovations in Information Technology Innovations in Information Technology, 2008. IIT 2008. International Conference on. :282-286 Dec, 2008

    Relation: 2008 International Conference on Innovations in Information Technology (IIT)

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  8. 8
    مؤتمر
    Fingerprint Clustering and its Application to Generate Class Code Using ART Neural Network

    المؤلفون: Gour, Bhupesh, Bandopadhyaya, T.K., Sharma, Sudhir

    المصدر: 2008 First International Conference on Emerging Trends in Engineering and Technology Emerging Trends in Engineering and Technology, 2008. ICETET '08. First International Conference on. :686-690 Jul, 2008

    Relation: 2008 1st International Conference on Emerging Trends in Engineering and Technology (ICETET)

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  9. 9
    مؤتمر
    Comparison of Kohonen's Self-Organizing Map algorithm and principal component analysis in the exploratory data analysis of a groundwater quality dataset

    المؤلفون: Peeters, Luk, Dassargues, Alain

    المساهمون: Aquapôle - AQUAPOLE, research center

    مصطلحات موضوعية: groudwater quality, exploratory data analysis, principal component analysis, Self-Organizing Map algorithm, Kohonen's Self-Organizing Map, SOMs, Engineering, computing & technology :: Geological, petroleum & mining engineering, Ingénierie, informatique & technologie :: Géologie, ingénierie du pétrole & des mines

    جغرافية الموضوع: international

    Relation: GeoENV2006 (2006)

    URL الوصول: https://orbi.uliege.be/handle/2268/3388

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  10. 10
    دورية أكاديمية
    High genetic differentiation of grapevine rootstock varieties determined by molecular markers and artificial neural networks

    المؤلفون: Marcia Oliveira Costa, Livia Santos Capel, Carlos Maldonado, Freddy Mora, Claudete Aparecida Mangolin, Maria de Fátima Pires da Silva Machado

    المصدر: Acta Scientiarum: Agronomy, Vol 42, Pp e43475-e43475 (2019)

    مصطلحات موضوعية: clustering methods, rapd-ssr loci, self-organizing map algorithm., Agriculture (General), S1-972

    وصف الملف: electronic resource

    Relation: http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/43475; https://doaj.org/toc/1679-9275; https://doaj.org/toc/1807-8621

    URL الوصول: https://doaj.org/article/6d851e77424c4f03ba426d9e453d6dbb

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