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Volumn 44, Issue 3, 2001, Pages 210-217

Comparison of five clustering algorithms to classify phytoplankton from flow cytometry data

Author keywords

Automatic cluster extraction; Clustering algorithms; Neural networks; Phytoplankton

Indexed keywords

ALGORITHM; ARTIFICIAL NEURAL NETWORK; CLUSTER ANALYSIS; CONFERENCE PAPER; ECOLOGY; FLOW CYTOMETRY; MULTIVARIATE ANALYSIS; PHYTOPLANKTON; PRIORITY JOURNAL;

EID: 0035396522     PISSN: 01964763     EISSN: None     Source Type: Journal    
DOI: 10.1002/1097-0320(20010701)44:3<210::AID-CYTO1113>3.0.CO;2-Y     Document Type: Conference Paper
Times cited : (33)

References (27)
  • 1
    • 0000136798 scopus 로고
    • Analytical flow cytometry and its application to marine microbial ecology
    • Sleigh MA, editor. Microbes in the sea. Chichester: Horwood
    • (1987) , pp. 139-166
    • Burkill, P.H.1
  • 17
    • 0002024412 scopus 로고
    • Knowing when to stop: Cluster concept-concept cluster
    • (1988) Coenoses , vol.3 , pp. 11-32
    • Dale, M.B.1
  • 23
  • 26
    • 0001794519 scopus 로고    scopus 로고
    • Artificial neural networks for pattern recognition
    • Fielding AH, editor. Machine learning methods for ecological applications. Boston: Kluwer
    • (1999) , pp. 37-87
    • Boddy, L.1    Morris, C.W.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.