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＜電子ブック＞
Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering / by Larisa Angstenberger
(International Series in Intelligent Technologies ; 17)

版	1st ed. 2001.
出版者	(Dordrecht : Springer Netherlands : Imprint: Springer)
出版年	2001
本文言語	英語
大きさ	XXII, 288 p : online resource
著者標目	*Angstenberger, Larisa author SpringerLink (Online service)
件　名	LCSH:Mathematical logic LCSH:Artificial intelligence LCSH:Computer vision FREE:Mathematical Logic and Foundations FREE:Artificial Intelligence FREE:Computer Vision
一般注記	1 Introduction -- 2 General Framework of Dynamic Pattern Recognition -- 3 Stages of the Dynamic Pattern Recognition Process -- 4 Dynamic Fuzzy Classifier Design with Point-Prototype Based Clustering Algorithms -- 5 Similarity Concepts for Dynamic Objects in Pattern Recognition -- 6 Applications of Dynamic Pattern Recognition Methods -- 7 Conclusions -- References -- Unsupervised Optimal Fuzzy Clustering Algorithm of Gath and Geva -- Description of Implemented Software Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering focuses on fuzzy clustering methods which have proven to be very powerful in pattern recognition and considers the entire process of dynamic pattern recognition. This book sets a general framework for Dynamic Pattern Recognition, describing in detail the monitoring process using fuzzy tools and the adaptation process in which the classifiers have to be adapted, using the observations of the dynamic process. It then focuses on the problem of a changing cluster structure (new clusters, merging of clusters, splitting of clusters and the detection of gradual changes in the cluster structure). Finally, the book integrates these parts into a complete algorithm for dynamic fuzzy classifier design and classification HTTP:URL=https://doi.org/10.1007/978-94-017-1312-2

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