clustering algorithm is one of key technologies for constructing hierarchical network structure and its quality directly affects performance of wireless self-organized network (WSON). In this paper study backgrounds o...
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In this paper a fuzzy quantization dequantization criterion is used to propose an evaluation technique to determine the appropriate clustering algorithm suitable for a particular data set. In general, the goodness of ...
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This project addresses the issues of finding the appropriate values for the constants or parameters used in any clustering algorithm for software maintenance. It is an attempt to reduce the human effort of substitutin...
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ISBN:
(纸本)9781450319010
This project addresses the issues of finding the appropriate values for the constants or parameters used in any clustering algorithm for software maintenance. It is an attempt to reduce the human effort of substituting random values in an algorithm and finding the right value for the constant by trial and error. This application implements a single objective genetic algorithm which solves the above mentioned issue in a pattern very similar to the human approach, but the computer solution is much more efficient and robust. Two clustering algorithms have also been implemented to interface with the proposed solution to study the behavior and verify the validity if the proposed solution. Experimental results show that the presented genetic-based solution is appropriate for this problem, as it tries different combinations and solutions and gives the values which in-turn helps the clustering algorithm to give optimal results. Copyright 2013 ACM.
A single linkage clustering algorithm adapted for points distributed over time (SLOT) is used to recover clusters from coplanar points associated with time parameters. Cluster number and shape determine separability a...
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ISBN:
(纸本)0818608455
A single linkage clustering algorithm adapted for points distributed over time (SLOT) is used to recover clusters from coplanar points associated with time parameters. Cluster number and shape determine separability and hence effectiveness of the algorithm. Performance in simulation experiments also depended on the probability of recording cluster points. SLOT links points observed at different times if they are within some limiting distance/ and the distance parameter becomes critical when detect-ability is low. Performance comparisons are made with other algorithms;and results are presented in the context of a rule-based expert system for solving problems involving cluster analysis of time-dependent spatial patterns.
The paper presents an evaluation of four clustering algorithms: k-means, average linkage, complete linkage, and Ward's method, with the latter three being different hierarchical methods. The quality of the cluster...
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Interactive visual analysis tools bring the ability of the real-time discovery of knowledge in large and complex datasets using visual analytics. It involves multiple iterations of data processing using various data h...
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Image segmentation deals with partitioning an input image into disjoint/non-overlapping regions. Among different segmentation algorithms, level set methods have been very popular. Less sensitivity to initialization, a...
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ISBN:
(纸本)9781424455614
Image segmentation deals with partitioning an input image into disjoint/non-overlapping regions. Among different segmentation algorithms, level set methods have been very popular. Less sensitivity to initialization, ability to split and merge the contour, and also, involving statistical inference have made level set even more accepted than similar methods like snakes. However, it is very time-consuming. To solve this problem, in this paper a fast variational approach is presented for texture segmentation. For this purpose, first a feature space based on non-linear diffusion is set up from CIE L*a*b* colour components. Then, this feature space is clustered by fusion of clustering algorithms. Finally, the produced cluster map is used in level set for contour evolution. As it is shown in the simulation results, our algorithm is robust in segmenting noisy texture. Also, it is faster than previous level set approaches for texture segmentation.
The article deals with the subject of mini-models (MMs) based on clustering algorithms. The mini-model method is a local regression algorithm that operates on some part of the input space called the mini-model domain ...
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Document clustering as an unsupervised approach extensively used to navigate, filter, summarize and manage large collection of document repositories like the World Wide Web (WWW). Recently, focuses in this domain shif...
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In the past years, microarray technologies have become a central tool in biological research. The extraction or identification of gene groups with similar expression pattern plays an important role in the analysis of ...
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