Aquatic biodiversity conservation zoning study based on the fuzzy clustering analysis: A case study of Tieling City, China

2020 ◽  
Vol 10 (7) ◽  
pp. 1654-1659
Author(s):  
Hengfei Wu ◽  
Guanglei Sheng ◽  
Lin Li

Multi-view fuzzy clustering analysis is often used for medical image segmentation such as brain MR image segmentation. However, in traditional multi-view clustering, it assumes that each view plays the same role to the final partition result, which omits the negative influences caused by noisy or weak views. In this paper, a novel entropy weighting based centralized clustering technique is proposed for multi-view datasets where the Shannon entropy is hired for view weight learning. Moreover, the centralized strategy is employed for collaborate learning. Extensive experiments show that the promising performance of our proposed clustering technique. More importantly, a case study on brain MR image segmentation indicates the application ability of our clustering technique.


2013 ◽  
Vol 12 (7) ◽  
pp. 1358-1365
Author(s):  
Yau-Ren Shiau ◽  
Ching-Hsing Tsai ◽  
Yung-Hsiang Hung ◽  
Jui-Huan Wu

2005 ◽  
Vol 23 (4) ◽  
pp. 1157-1163 ◽  
Author(s):  
M. Sridharan ◽  
N. Gururajan ◽  
A. M. S. Ramasamy

Abstract. The utility of fuzzy set theory in cluster analysis and pattern recognition has been evolving since the mid 1960s, in conjunction with the emergence and evolution of computer technology. The classification of objects into categories is the subject of cluster analysis. The aim of this paper is to employ Fuzzy-clustering technique to examine the interrelationship of geomagnetic coastal and other effects at Indian observatories. Data from the observatories used for the present studies are from Alibag on the West Coast, Visakhapatnam and Pondicherry on the East Coast, Hyderabad and Nagpur as central inland stations which are located far from either of the coasts; all the above stations are free from the influence of the daytime equatorial electrojet. It has been found that Alibag and Pondicherry Observatories form a separate cluster showing anomalous variations in the vertical (Z)-component. H- and D-components form different clusters. The results are compared with the graphical method. Analytical technique and the results of Fuzzy-clustering analysis are discussed here.


2014 ◽  
Vol 513-517 ◽  
pp. 1540-1544
Author(s):  
Li Hua Zhang ◽  
Wei Liu

Today's society is a society of information explosion, the popularity of the Internet and development bring a lot of convenience to people, people can easily get a lot of information on the network, however, facing so many information, people prone to the problems of "information overload" and "resources disorientation. Therefore, the recommended system came into being, the recommendation system can provide people with the most in need and most concern to avoid the time of the search and comparison. This article intends to use the very mature recommendation system in the field of electronic commerce to distance education system and promotes personalized learning, shifting the traditional "what teachers teach, what students receive" to "what the students need, what the system provides, which is consistent of constructivism study philosophy. The analysis of users interested as the basis of the recommendation system, users clustering is very important, the objective classification of fuzzy clustering analysis can recommend for users to enjoy high-quality service.


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