Statistical and Fuzzy Clustering Methods and their Application to Clustering Provinces of Iraq based on Agricultural Products

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
The important approaches to statistical and fuzzy clustering are reviewed and compared, and their applications to an agricultural problem based on a real-world data are investigated. The methods employed in this study includes some hierarchical clustering and non-hierarchical clustering methods and Fuzzy C-Means method. As a case study, these methods are then applied to cluster 15 provinces of Iraq based on some agricultural crops. Finally, a comparative and evaluation study of different statistical and fuzzy clustering methods is performed. The obtained results showed that, based on the Silhouette criterion and Xie-Beni index, fuzzy c-means method is the best one among all reviewed methods
Language:
English
Published:
AUT Journal of Mathematics and Computing, Volume:1 Issue: 1, Feb 2020
Pages:
101 to 112
https://www.magiran.com/p2450899  
سامانه نویسندگان
  • Corresponding Author (2)
    Seyed Mahmoud Taheri
    (1378) دکتری آمار استنباطی، دانشگاه شیراز
    Taheri، Seyed Mahmoud
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