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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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[1] Y. Al-Fahad and T. Abbas, GIS Center Central Bureau of Statistics (NBS), Iraq, 2011.
[2] N. Aguilar-Gallegos, M. Munoz-Rodriguez, H. Santoyo-Cortes, J. Aguilar-Avila, and L. Klerkx, Information Networks that Generate Economic Value: A Study on Clusters of Adopters of New or Improved Technologies and Practices among Oil Palm Growers in Mexico, Agricultural Systems, vol. 135, pp. 122-132, 2015.
[3] A. Ansari, P. S. Sikarwar, S. Lade, H. K. Yadav and S. A. Randade, Genetic Diversity in Germplasm of Cluster Bean, an Important Food and an Industrial Legume Crop, J. Agr. Sci. Tech., vol. 18, pp. 1393-1406, 2016.
[4] D. J. Bora and A. K. Gupta, A Comparative Study between Fuzzy Clustering Algorithm and Hard Clustering Algorithm, International Journal of Computer Trends and Technology, vol. 10, pp. 785-790, 2014.
[5] C. T. Chang, J. Z. C. Lai and M. D. Jeng, A Fuzzy K-means Clustering Algorithm Using Cluster Center Displacement, Journal of Information Science and Engineering, vol. 27, pp. 995-1009, 2011.
[6] S. Chattopadhyay, D. K. Pratihar, S. C. D Sarkar, A Comparative Study of Fuzzy C-Means Algorithm and Entropy Based Fuzzy Clustering Algorithms, Computing and Informatics, vol.30, pp. 701–720, 2011.
[7] R. Dave, Fuzzy Shell-Clustering and Applications to Circle Detection in Digital Images, lnt. J. General Systems, vol. 16,. pp. 343-355, 1989.
[8] J. V. De Oliveira and W. Pedrycz, Advances in Fuzzy Clustering and Its Applications, John Wiley and Sons, New York, 2007.
[9] M. Fajardo, A. Mc. Bratney and Whelan, Fuzzy Clustering of Vis–NIR Spectra for the Objective Recognition of Soil Morphological Horizons in Soil Profiles, Geoderma, vol. 263, pp. 244–253, 2016.
[10] M. B. Ferraro, and P. Giordani, A Toolbox for Fuzzy Clustering Using the R Programming Language, Fuzzy Sets and Systems, vol. 279, pp. 1–16, 2015.
[11] G. Gan, C. Ma and J. Wu, Data Clustering Theory, Algorithms, and Applications, SIAM, Virginia, 2007.
[12] C. Gomathi and K. Velusamy, Solving Fuzzy Clustering Problem Using Hybridization of Fuzzy C-Means and Fuzzy Bee Colony Optimization, International Journal of Computer Engineering and Applications, vol. 12, pp. 317–324, 2018.
[13] N. Grover, A Study of Various Fuzzy Clustering Algorithms, International Journal of Engineering Research, vol. 3, pp. 177–181, 2014.
[14] Z. Huang and M. Ng, A Fuzzy K-Modes Algorithm for Clustering Categorical Data. IEEE Transactions on Fuzzy Systems, vol.7, pp.446–452, 1999.
[15] J. G. Klir and B. Yuan, Fuzzy Sets and Fuzzy Logic: Theory and Applications, Prentice Hall, New York, 1995.
[16] P. Kostov and S. Mc Erlean, Using the Mixtures- of Distributions Technique for the Classification of Farms into Representative Farms. Agricultural Systems, vol. 88, pp. 528-537, 2006.
[17] E. Mansour, A. B. Khaled, T. Triki, M. Abid, K. Bachar, and A. Ferchichi, Evaluation of Genetic Diversity among South Tunisian Pomegranate Accessions Using Fruit Traits and RAPD Markers. J. Agr. Sci. Tech., vol. 17, pp. 109-119, 2015.
[18] B. Panda, S. Sahoo, and S. K. Patnaik, A Comparative Study of Hard and Soft Clustering Using Swarm Optimization: International Journal of Scientific & Engineering Research, vol. 4, pp. 785- 790, 2013.
[19] P. J. Rousseeuw, Silhouettes A Graphical Aid to the Interpretation and Validation of Cluster Analysis, Journal of Computational and Applied Mathematics, vol. 20, pp. 53-65, 1987.
[20] A. C. Rencher, Methods of Multivariate Analysis, John Wiley and Sons, New York, 2002.
[21] H. Timm, C. Borgelt, C. Doring, and R. Kruse, An Extension to Possibilistic Fuzzy Cluster Analysis, Fuzzy Sets and Systems, 147, 3–16, 2004.
[22] T. Volmurgan, Austria Performance Comparison Between K-means and Fuzzy C- means, Wulfenia Journal Using Arbitrary Data Points, vol. 19, pp. 1-8, 2012.
[23] R. Suganya, and R. Shanthi, Fuzzy C- Means Algorithm - A Review, International Journal of Scientific and Research Publications, vol. 2, pp. 440-442, 2012.
[24] X.L. Xie, and G. Beni, A validity measure for fuzzy clustering, IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 8, pp. 841-847, 1991.
[25] M. S. Yang, Convergence Properties of the Generalized Fuzzy C-Means Clustering Algorithms, Computer Math. Appl, vol. 25, pp. 3-11, 1993. | ||
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