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Pattern Recognition with Fuzzy Objective Function Algorithms
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Citations
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Journal ArticleDOI
Cluster analysis of multiple planetary flow regimes
Kingtse C. Mo,Michael Ghil +1 more
TL;DR: In this article, a modified cluster analysis method was developed to identify spatial patterns of planetary flow regimes, and to study transitions between them, applied first to a simple deterministic model and second to Northern Hemisphere (NH) 500 mb data.
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Fuzzy image clustering incorporating spatial continuity
TL;DR: In this paper, a spatial fuzzy clustering algorithm that exploits the spatial contextual information in image data is presented, which is adaptive to the image content in the sense that influence from the neighbouring pixels is suppressed in nonhomogeneous regions in the image.
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Fuzzy shell-clustering and applications to circle detection in digital images
TL;DR: The FSC algorithm is shown to be superior to the HT method with regards to memory requirement and computation time and to be successful even if only a part of a circular shape is present in the image.
Journal ArticleDOI
A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms
TL;DR: A survey of 45 different recent algorithms proposed in the literature between 2008 and 2016 to handle computationally expensive multiobjective optimization problems and identifies and discusses some promising elements and major issues among algorithms in the Literature related to using an approximation and numerical settings used.
Book ChapterDOI
Fuzzy C-Means (FCM) Clustering Algorithm: A Decade Review from 2000 to 2014
TL;DR: A comprehensive survey on FCM and its applications in more than one decade has been carried out to show the efficiency and applicability in a mixture of domains and to encourage new researchers to make use of this simple algorithm.
References
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Journal ArticleDOI
Nearest neighbor pattern classification
Thomas M. Cover,Peter E. Hart +1 more
TL;DR: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
Book
Introduction to Statistical Pattern Recognition
TL;DR: This completely revised second edition presents an introduction to statistical pattern recognition, which is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field.
A fuzzy relative of the isodata process and its use in detecting compact well-separated clusters
TL;DR: In this paper, two fuzzy versions of the k-means optimal, least squared error partitioning problem are formulated for finite subsets X of a general inner product space, and the extremizing solutions are shown to be fixed points of a certain operator T on the class of fuzzy, k-partitions of X, and simple iteration of T provides an algorithm which has the descent property relative to the LSE criterion function.