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Volumn 6954 LNAI, Issue , 2011, Pages 337-346

Application of gravitational search algorithm on data clustering

Author keywords

Data clustering; Gravitational search algorithm

Indexed keywords

CANDIDATE SOLUTION; CLUSTERING PROBLEMS; CUSTOMER ANALYSIS; DATA CLUSTERING; DATA CLUSTERING ALGORITHM; DATA COMPACTION; DATA SETS; DATA SUMMARIZATIONS; FRAUD DETECTION; GLOBALOPTIMUM; INITIAL STATE; K-MEANS; K-MEANS ALGORITHM; LOCAL OPTIMA; MAIN TASKS; PARTICLE SWARM OPTIMIZATION ALGORITHM; PROBLEM SPACE; SEARCH ALGORITHMS; TEXT CLUSTERING;

EID: 80054069436     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-24425-4_44     Document Type: Conference Paper
Times cited : (60)

References (17)
  • 2
    • 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
  • 6
    • 0021202650 scopus 로고
    • K-Means-Type Algorithms: A Generalized Convergence Theorem and Characterization of Local Optimality
    • Selim, S.Z., Ismail, M.A.: K-Means-Type Algorithms: A Generalized Convergence Theorem and Characterization of Local Optimality, IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-6, 81-87 (1984)
    • (1984) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.PAMI-6 , pp. 81-87
    • Selim, S.Z.1    Ismail, M.A.2
  • 7
    • 0026359031 scopus 로고
    • A simulated annealing algorithm for the clustering problem
    • Selim, S.Z., Alsultan, K.: A simulated annealing algorithm for the clustering problem. Pattern Recognition 24, 1003-1008 (1991)
    • (1991) Pattern Recognition , vol.24 , pp. 1003-1008
    • Selim, S.Z.1    Alsultan, K.2
  • 8
    • 0029478402 scopus 로고
    • A Tabu search approach to the clustering problem
    • Al-Sultan, K.S.: A Tabu search approach to the clustering problem. Pattern Recognition 28, 1443-1451 (1995)
    • (1995) Pattern Recognition , vol.28 , pp. 1443-1451
    • Al-Sultan, K.S.1
  • 9
    • 0033715579 scopus 로고    scopus 로고
    • Genetic algorithm-based clustering technique
    • Maulik, U., Bandyopadhyay, S.: Genetic algorithm-based clustering technique. Pattern Recognition 33, 1455-1465 (2000)
    • (2000) Pattern Recognition , vol.33 , pp. 1455-1465
    • Maulik, U.1    Bandyopadhyay, S.2
  • 13
    • 34250683045 scopus 로고    scopus 로고
    • Application of honey-bee mating optimization algorithm on clustering
    • Fathian, M., Amiri, B., Maroosi, A.: Application of honey-bee mating optimization algorithm on clustering. Applied Mathematics and Computation 190, 1502-1513 (2007)
    • (2007) Applied Mathematics and Computation , vol.190 , pp. 1502-1513
    • Fathian, M.1    Amiri, B.2    Maroosi, A.3
  • 14
    • 77957901422 scopus 로고    scopus 로고
    • A novel clustering approach: Artificial Bee Colony (ABC) algorithm
    • Karaboga, D., Ozturk, C.: A novel clustering approach: Artificial Bee Colony (ABC) algorithm. Applied Soft Computing 11, 652-657
    • Applied Soft Computing , vol.11 , pp. 652-657
    • Karaboga, D.1    Ozturk, C.2
  • 15
    • 64549119687 scopus 로고    scopus 로고
    • GSA: A Gravitational Search Algorithm
    • Rashedi, E., Nezamabadi-pour, H., Saryazdi, S.: GSA: A Gravitational Search Algorithm. dgd 179, 2232-2248 (2009)
    • (2009) Dgd , vol.179 , pp. 2232-2248
    • Rashedi, E.1    Nezamabadi-pour, H.2    Saryazdi, S.3
  • 16
    • 33846661354 scopus 로고    scopus 로고
    • K-harmonic means data clustering with simulated annealing heuristic
    • Güngör, Z., Ünler, A.: K-harmonic means data clustering with simulated annealing heuristic. Applied Mathematics and Computation 184, 199-209 (2007)
    • (2007) Applied Mathematics and Computation , vol.184 , pp. 199-209
    • Güngör, Z.1    Ünler, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.