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Statistical and fuzzy clustering methods and their application to clustering provinces of Iraq based on agricultural products | ||
| AUT Journal of Mathematics and Computing | ||
| مقاله 10، دوره 1، شماره 1، اردیبهشت 2020، صفحه 101-112 اصل مقاله (700.84 K) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22060/ajmc.2019.14873.1013 | ||
| نویسندگان | ||
| Israa Atiyah1؛ Seyed Mahmoud Taheri* 2 | ||
| 1Faculty of Science, University of Al-Qadisiyah, Iraq | ||
| 2School of Engineering Science, College of Engineering, University of Tehran | ||
| چکیده | ||
| 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 | ||
| کلیدواژه‌ها | ||
| Hierarchical Clustering؛ Non-Hierarchical Clustering؛ Fuzzy C-Means Clustering | ||
| مراجع | ||
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