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Volumn 10, Issue 3, 2006, Pages 244-256

Hierarchical FCM in a stepwise discovery of structure in data

Author keywords

Clustering tree; Computational complexity; Computing aspects; Data analysis; FCM tree structure; Hierarchical FCM; Mapping criterion; Problem decomposition; Refinement; Stepwise structure discovery

Indexed keywords


EID: 29444438571     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-005-0478-8     Document Type: Article
Times cited : (25)

References (16)
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    • Campos, M.M.1    Carpenter, G.A.2
  • 7
    • 0037118555 scopus 로고    scopus 로고
    • A fuzzy hybrid hierarchical clustering method with a new criterion to find the optimal partition
    • Devillez A, Billaudel P, Lecolier GV (2002) A fuzzy hybrid hierarchical clustering method with a new criterion to find the optimal partition. Fuzzy Sets Syst 128:323-338
    • (2002) Fuzzy Sets Syst. , vol.128 , pp. 323-338
    • Devillez, A.1    Billaudel, P.2    Lecolier, G.V.3
  • 10
    • 9144269130 scopus 로고    scopus 로고
    • Adaptive topological tree structure for document organization and visualization
    • (to appear)
    • Freeman RT, Yin H (2004) Adaptive topological tree structure for document organization and visualization. Neural Netw (to appear)
    • (2004) Neural Netw.
    • Freeman, R.T.1    Yin, H.2
  • 11
    • 0003959189 scopus 로고
    • Vector quantization and signal compression
    • Kluwer, Boston
    • Gersho A, Gray RM (1992) Vector quantization and signal compression. Kluwer, Boston
    • (1992)
    • Gersho, A.1    Gray, R.M.2
  • 12
    • 0000212165 scopus 로고    scopus 로고
    • About the use of fuzzy clustering techniques for fuzzy model identification
    • Gomez-Skarmeta AF, Delgado M, Vila MA (1999) About the use of fuzzy clustering techniques for fuzzy model identification. Fuzzy Sets Syst 1069:179-188
    • (1999) Fuzzy Sets Syst. , vol.1069 , pp. 179-188
    • Gomez-Skarmeta, A.F.1    Delgado, M.2    Vila, M.A.3
  • 13
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    • Speeding up fuzzy c-means using a hierarchical data organization to control the precision of membership calculation
    • Hoppner F (2002) Speeding up fuzzy c-means using a hierarchical data organization to control the precision of membership calculation. Fuzzy Sets Systems 128:365-376
    • (2002) Fuzzy Sets Systems , vol.128 , pp. 365-376
    • Hoppner, F.1
  • 16
    • 0032122726 scopus 로고    scopus 로고
    • Conditional fuzzy clustering in the design of radial basis function neural networks
    • Pedrycz W (1998) Conditional fuzzy clustering in the design of radial basis function neural networks. IEEE Trans Neural Netw 9:601-612
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    • Pedrycz, W.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.