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Volumn 39, Issue 6, 2005, Pages 8-17

A new approach to the problem of clustering using the fuzzy joint points method

Author keywords

Fuzzy clustering; Fuzzy conical point; Fuzzy joint points (FJP); Fuzzy joint set

Indexed keywords

ALGORITHMS; COMPUTATIONAL GEOMETRY; COMPUTER SCIENCE; HIERARCHICAL SYSTEMS;

EID: 33747058824     PISSN: 01464116     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (8)

References (15)
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  • 4
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  • 8
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    • On cluster validity for the fuzzy c-means models
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  • 10
    • 0031192645 scopus 로고    scopus 로고
    • An investigation of mountain method clustering for large data sets
    • R.P. Velthuizen, L.O. Hall, L.P. Clarke, and M.L. Silbiger, "An investigation of mountain method clustering for large data sets," Pattern Recognition, vol. 30, no. 7, pp. 1121-1135, 1997.
    • (1997) Pattern Recognition , vol.30 , Issue.7 , pp. 1121-1135
    • Velthuizen, R.P.1    Hall, L.O.2    Clarke, L.P.3    Silbiger, M.L.4
  • 11
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    • Approximate clustering via the mountain method
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  • 12
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    • A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters
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    • Dunn, J.C.1
  • 13
    • 0032628736 scopus 로고    scopus 로고
    • On distance measures for the fuzzy K-Mean algorithm for joint data
    • R.E. Hammah and J.H. Curran, "On distance measures for the fuzzy K-Mean algorithm for joint data," Rock Mech. Rock Engng., vol. 32, no. 1, pp. 1-27, 1999.
    • (1999) Rock Mech. Rock Engng. , vol.32 , Issue.1 , pp. 1-27
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  • 14
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    • Fuzzy clustering procedures for conical fuzzy vector data
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    • Yang, M.S.1    Liu, H.H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.