The possibilistic C-means (PCM) clustering algorithm is shown to be superior to the conventional fuzzy C-means (FCM) clustering algorithms. We attack several unsolved issues in applying the possibilistic approach to fuzzy clustering. An initial independent and highly noise resistant possibilistic clustering algorithm, named the novel possibilistic C-means (NPCM) clustering algorithm, is developed.<>


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    An initial independent and highly noise-resistant fuzzy possibilistic clustering algorithm


    Beteiligte:
    Xinhua Zhuang (Autor:in) / Yunxin Zhao (Autor:in) / Yan Huang (Autor:in) / Tong Huang (Autor:in)


    Erscheinungsdatum :

    01.01.1994


    Format / Umfang :

    320891 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    An Initial Independent and Highly Noise-Resistant Fuzzy Possibilistic Clustering Algorithm

    Zhuang, X. / Zhao, Y. / Huang, Y. et al. | British Library Conference Proceedings | 1994



    Automatic Segmentation of Liver Tumour using a Possibilistic Alternative Fuzzy C-Means Clustering

    Kumar, Sikamony S. / Moni, Rama S. / Rajeesh, Jayapathy | British Library Online Contents | 2013



    Automatic Segmentation of Liver Tumour using a Possibilistic Alterllative F1lzzy C-Means Clustering

    Kumar, S.S. / Moni, R.S. / Rajeesh, J. | British Library Online Contents | 2013