Innovations in Fuzzy Clustering Theory and Applications /

There is a great interest in clustering techniques due to the vast amount of data generated in every field including business, health, science, engineering, aerospace, management and so on. It is essential to extract useful information from the data. Clustering techniques are widely used in pattern...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Sato-Ilic, Mika (Συγγραφέας), Jain, Lakhmi C. (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006.
Σειρά:Studies in Fuzziness and Soft Computing, 205
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Sato-Ilic, Mika.  |e author. 
245 1 0 |a Innovations in Fuzzy Clustering  |h [electronic resource] :  |b Theory and Applications /  |c by Mika Sato-Ilic, Lakhmi C. Jain. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg,  |c 2006. 
300 |a XIII, 151 p.  |b online resource. 
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490 1 |a Studies in Fuzziness and Soft Computing,  |x 1434-9922 ;  |v 205 
505 0 |a to Fuzzy Clustering -- Fuzzy Clustering based Principal Component Analysis -- Fuzzy Clustering based Regression Analysis -- Kernel based Fuzzy Clustering -- Evaluation of Fuzzy Clustering -- Self-Organized Fuzzy Clustering. 
520 |a There is a great interest in clustering techniques due to the vast amount of data generated in every field including business, health, science, engineering, aerospace, management and so on. It is essential to extract useful information from the data. Clustering techniques are widely used in pattern recognition and related applications. The research monograph presents the most recent advances in fuzzy clustering techniques and their applications. The following contents are included: Introduction to Fuzzy Clustering Fuzzy Clustering based Principal Component Analysis Fuzzy Clustering based Regression Analysis Kernel based Fuzzy Clustering Evaluation of Fuzzy Clustering Self-Organized Fuzzy Clustering This book is directed to the computer scientists, engineers, scientists, professors and students of engineering, science, computer science, business, management, avionics and related disciplines. 
650 0 |a Mathematics. 
650 0 |a Artificial intelligence. 
650 0 |a Mathematical logic. 
650 0 |a Applied mathematics. 
650 0 |a Engineering mathematics. 
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650 2 4 |a Mathematical Logic and Foundations. 
650 2 4 |a Appl.Mathematics/Computational Methods of Engineering. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
700 1 |a Jain, Lakhmi C.  |e author. 
710 2 |a SpringerLink (Online service) 
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776 0 8 |i Printed edition:  |z 9783540343561 
830 0 |a Studies in Fuzziness and Soft Computing,  |x 1434-9922 ;  |v 205 
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950 |a Engineering (Springer-11647)