Using the Hopfield– Fuzzy C Means Algorithm for Clustering of People based on Food Insecurity and Obesity in the Northwest of Iran
It is commonly recognized that food insecurity and obesity is the major sections of academic researches, but the activities' rate of food insecurity and surveillance is always Low. Based on food insecurity and obesity’ characteristics, in this paper attempt are made to present a model based on...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Joint Coordination Centre of the World Bank assisted National Agricultural Research Programme (NARP)
2013-05-01
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| Series: | Journal of Applied Sciences and Environmental Management |
| Online Access: | https://www.Ajol.Info/index.php/jasem/article/view/88626 |
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| Summary: | It is commonly recognized that food insecurity and obesity is the major sections of academic researches, but the activities' rate of food insecurity and surveillance is always Low. Based on food insecurity and obesity’ characteristics, in this paper attempt are made to present a model based on Hopfield– fuzzy C Means clustering algorithm. Firstly, it is capable of identifying the reasons behind the emergence of the present status. Secondly, the suggested model must represent the clustering of the people based on food insecurity and surveillance in different levels. Finally, it tests the validity of the suggested model with comparing by other models (Hopfield–K-Means, K-Means, and fuzzy C Means). @JASEM
Keywords: Learning, Clustering, Algorithm, Hopfield
J. Appl. Sci. Environ. Manage. Dec, 2011, Vol. 15 (4) 635 - 641 |
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| ISSN: | 2659-1502 2659-1499 |