Statistical and fuzzy clustering methods and their application to clustering provinces of Iraq based on agricultural products
نویسندگان
1 Faculty of Science, University of Al-Qadisiyah, Iraq
2 School of Engineering Science, College of Engineering, University of Tehran
doi
10.22060/ajmc.2019.14873.1013چکیده
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
