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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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2006.
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| Edición: | 1st ed. 2006. |
| Colección: | Studies in Fuzziness and Soft Computing,
205 |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 100 | 1 | |a Sato-Ilic, Mika. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Innovations in Fuzzy Clustering |h [electronic resource] : |b Theory and Applications / |c by Mika Sato-Ilic. |
| 250 | |a 1st ed. 2006. | ||
| 264 | 1 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg : |b Imprint: Springer, |c 2006. | |
| 300 | |a XIII, 151 p. |b online resource. | ||
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| 490 | 1 | |a Studies in Fuzziness and Soft Computing, |x 1860-0808 ; |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 Mathematical logic. | |
| 650 | 0 | |a Engineering mathematics. | |
| 650 | 0 | |a Engineering-Data processing. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 1 | 4 | |a Mathematical Logic and Foundations. |
| 650 | 2 | 4 | |a Mathematical and Computational Engineering Applications. |
| 650 | 2 | 4 | |a Artificial Intelligence. |
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| 776 | 0 | 8 | |i Printed edition: |z 9783642070723 |
| 776 | 0 | 8 | |i Printed edition: |z 9783540824213 |
| 776 | 0 | 8 | |i Printed edition: |z 9783540343561 |
| 830 | 0 | |a Studies in Fuzziness and Soft Computing, |x 1860-0808 ; |v 205 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/3-540-34357-1 |z Texto Completo |
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