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Cites:

1

Information Journal Paper

Title

OPTIMIZATION OF FUZZY CLUSTERING CRITERIA BY A HYBRID PSO AND FUZZY C-MEANS CLUSTERING ALGORITHM

Pages

  1-14

Keywords

PARTICLE SWARM OPTIMIZATION (PSO)Q2
FUZZY C-MEANS (FCM)Q2

Abstract

 This paper presents an efficient hybrid method, namely fuzzy particle swarm optimization (FPSO) and fuzzy c-means (FCM) algorithms, to solve the FUZZY CLUSTERING problem, especially for large sizes. When the problem becomes large, the FCM algorithm may result in uneven distribution of data, making it difficult to find an optimal solution in reasonable amount of time. The PSO algorithm does find a good or near-optimal solution in reasonable time, but we show that its performance may be improved by seeding the initial swarm with the result of the c-means algorithm. Various clustering simulations are experimentally compared with the FCM algorithm in order to illustrate the efficiency and ability of the proposed algorithms.

Cites

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  • Cite

    APA: Copy

    MAHDIZADEH, E., SADINEZHAD, S., & TAVAKOLI MOGHADAM, R.. (2008). OPTIMIZATION OF FUZZY CLUSTERING CRITERIA BY A HYBRID PSO AND FUZZY C-MEANS CLUSTERING ALGORITHM. IRANIAN JOURNAL OF FUZZY SYSTEMS, 5(3), 1-14. SID. https://sid.ir/paper/113265/en

    Vancouver: Copy

    MAHDIZADEH E., SADINEZHAD S., TAVAKOLI MOGHADAM R.. OPTIMIZATION OF FUZZY CLUSTERING CRITERIA BY A HYBRID PSO AND FUZZY C-MEANS CLUSTERING ALGORITHM. IRANIAN JOURNAL OF FUZZY SYSTEMS[Internet]. 2008;5(3):1-14. Available from: https://sid.ir/paper/113265/en

    IEEE: Copy

    E. MAHDIZADEH, S. SADINEZHAD, and R. TAVAKOLI MOGHADAM, “OPTIMIZATION OF FUZZY CLUSTERING CRITERIA BY A HYBRID PSO AND FUZZY C-MEANS CLUSTERING ALGORITHM,” IRANIAN JOURNAL OF FUZZY SYSTEMS, vol. 5, no. 3, pp. 1–14, 2008, [Online]. Available: https://sid.ir/paper/113265/en

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