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Generalizations of Information Granules

2003
In this chapter, we discuss various extensions of the fundamental formal environments of granular computing and elaborate on a series of synergistic interactions arising between them. The first trend is motivated by the complexity and diversity of the granular aspect of information.
Andrzej Bargiela, Witold Pedrycz
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Information Granules for Intelligent Knowledge Structures

2007
The 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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Interpretability constraints for fuzzy information granulation

Information Sciences, 2008
Information granules are complex entities that arise in the process of abstraction of data and derivation of knowledge. The automatic generation of information granules from data is an important task, since it gives to machines the ability of acquiring knowledge that can be communicated to users.
Corrado Mencar, Anna Maria Fanelli
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Information Granules in Application to Image Recognition

2015
The paper concerns specific problems of color digital image recognition by use of the concept of fuzzy and rough granulation. This idea employs information granules that contain pieces of knowledge about digital pictures such as color, location, size, and shape of an object to be recognized.
Krzysztof Wiaderek   +2 more
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Theory and Practice on Information Granule Matrix

2006
In 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, 2018
A 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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An Improved Clustering Algorithm for Information Granulation

2005
C-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

2019
Information 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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Information Granulation With Rectangular Information Granules and Its Application in Time-Series Similarity Measurement

IEEE Transactions on Fuzzy Systems, 2022
Sheng Du   +4 more
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Advantages of Information Granulation in Clustering Algorithms

2013
Clustering 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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