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Volumn 241 CCIS, Issue , 2011, Pages 383-388

Data clustering using big bang-big crunch algorithm

Author keywords

Big Bang Big Crunch algorithm; Cluster analysis

Indexed keywords

A-CENTER; BIG BANG; BIG CRUNCH; BIG CRUNCH THEORY; CANDIDATE SOLUTION; DATA CLUSTERING; MINIMAL COST; OPTIMIZATION METHOD; OPTIMIZATION PROBLEMS; RANDOMLY DISTRIBUTED; REPRESENTATIVE POINT; SEARCH SPACES;

EID: 83755162323     PISSN: 18650929     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-27337-7_36     Document Type: Conference Paper
Times cited : (57)

References (16)
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  • 2
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    • Optimal design of Schwedler and ribbed domes via hybrid Big Bang-Big Crunch algorithm
    • Kaveh, A., Talatahari, S.: Optimal design of Schwedler and ribbed domes via hybrid Big Bang-Big Crunch algorithm. Journal of Constructional Steel Research 66, 412-419
    • Journal of Constructional Steel Research , vol.66 , pp. 412-419
    • Kaveh, A.1    Talatahari, S.2
  • 3
    • 67651210697 scopus 로고    scopus 로고
    • Size optimization of space trusses using Big Bang-Big Crunch algorithm
    • Kaveh, A., Talatahari, S.: Size optimization of space trusses using Big Bang-Big Crunch algorithm. Computers & Structures 87, 1129-1140 (2009)
    • (2009) Computers & Structures , vol.87 , pp. 1129-1140
    • Kaveh, A.1    Talatahari, S.2
  • 5
    • 78049426074 scopus 로고    scopus 로고
    • Big Bang-Big Crunch optimization for parameter estimation in structural systems
    • Tang, H., Zhou, J., Xue, S., Xie, L.: Big Bang-Big Crunch optimization for parameter estimation in structural systems. Mechanical Systems and Signal Processing 24, 2888-2897
    • Mechanical Systems and Signal Processing , vol.24 , pp. 2888-2897
    • Tang, H.1    Zhou, J.2    Xue, S.3    Xie, L.4
  • 7
    • 67649403091 scopus 로고    scopus 로고
    • Single point iterative weighted fuzzy C-means clustering algorithm for remote sensing image segmentation
    • Fan, J., Han, M., Wang, J.: Single point iterative weighted fuzzy C-means clustering algorithm for remote sensing image segmentation. Pattern Recognition 42, 2527-2540 (2009)
    • (2009) Pattern Recognition , vol.42 , pp. 2527-2540
    • Fan, J.1    Han, M.2    Wang, J.3
  • 9
    • 36148984621 scopus 로고    scopus 로고
    • A recommender system using GA K-means clustering in an online shopping market
    • Kim, K.-J., Ahn, H.: A recommender system using GA K-means clustering in an online shopping market. Expert Systems with Applications 34, 1200-1209 (2008)
    • (2008) Expert Systems with Applications , vol.34 , pp. 1200-1209
    • Kim, K.-J.1    Ahn, H.2
  • 10
    • 44449147811 scopus 로고    scopus 로고
    • MRI brain image segmentation and bias field correction based on fast spatially constrained kernel clustering approach
    • Liao, L., Lin, T., Li, B.: MRI brain image segmentation and bias field correction based on fast spatially constrained kernel clustering approach. Pattern Recognition Letters 29, 1580-1588 (2008)
    • (2008) Pattern Recognition Letters , vol.29 , pp. 1580-1588
    • Liao, L.1    Lin, T.2    Li, B.3
  • 14
    • 0000014486 scopus 로고
    • Cluster analysis of multivariate data: Efficiency versus interpretability of classifications
    • Forgy, E.W.: Cluster analysis of multivariate data: efficiency versus interpretability of classifications. Biometrics 21, 2 (1965)
    • (1965) Biometrics , vol.21 , pp. 2
    • Forgy, E.W.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.