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Theory and Practice on Information Granule Matrix
2006In this paper, a new framework called information granule matrix is suggested to illustrate a given granule sample for showing its information structure. The new framework does not any extra condition but the observations. An information granule matrix can be turned into a fuzzy relation matrix for fuzzy inference.
Ye Xue, Chongfu Huang
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Information granules in image histogram analysis
Computerized Medical Imaging and Graphics, 2018A concept of granular computing employed in intensity-based image enhancement is discussed. First, a weighted granular computing idea is introduced. Then, the implementation of this term in the image processing area is presented. Finally, multidimensional granular histogram analysis is introduced.
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Information Granules for Intelligent Knowledge Structures
2007The premise of this paper is that the acquisition, aggregation, merging and use of information requires some new ideas, tools and techniques which can simplify the construction, analysis and use of what we call ephemeral knowledge structures. Ephemeral knowledge structures are used and constructed by granular agents.
Patrick Doherty 0001 +2 more
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An Improved Clustering Algorithm for Information Granulation
2005C-means clustering is a popular technique to classify unlabeled data into dif-ferent categories. Hard c-means (HCM), fuzzy c-means (FCM) and rough c-means (RCM) were proposed for various applications. In this paper a fuzzy rough c-means algorithm (FRCM) is present, which integrates the advantage of fuzzy set theory and rough set theory. Each cluster is
Qinghua Hu, Daren Yu
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An Investigation of Information Granulation Techniques in Cybersecurity
2019Information Granulation in the context of Granular Computing provides a viable alternative for finding solutions to complex problems using granules. Issues such as intrusions, malware exigencies, spam and user unauthorized access still remain challenging in cybersecurity.
Sani Suleiman Isah +3 more
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Advantages of Information Granulation in Clustering Algorithms
2013Clustering is a part of data mining domain. Its task is to identify groups consisting of similar data objects according to defined similarity criterion. One of the most common problems in this field is the time complexity of algorithms. Reducing the time of processing is particularly important due to constantly growing size of present databases ...
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A Study of Information Granules
2007 IEEE International Conference on Granular Computing (GRC 2007), 2007openaire +1 more source