Cluster Analysis for Data Mining and System Identification

Janos Abonyi

Langue: Anglais

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Co-auteur:

Janos Abonyi

enCouverture rigide978376437987222 juin 2007303 pages

Résumé

The aim of this book is to illustrate that advanced fuzzy clustering algorithms can be used not only for partitioning of the data, but it can be used for visuali- tion,regression,classi?cationandtime-seriesanalysis,hence fuzzy cluster analysis is a good approach to solve complex data mining and system identi?cation pr- lems.

This book presents new approaches to data mining and system identification. Algorithms that can be used for the clustering of data have been overviewed. New techniques and tools are presented for the clustering, classification, regression and visualization of complex datasets. Special attention is given to the analysis of historical process data, tailored algorithms are presented for the data driven modeling of dynamical systems, determining the model order of nonlinear input-output black box models, and the segmentation of multivariate time-series. The main methods and techniques are illustrated through several simulated and real-world applications from data mining and process engineering practice.

The book is aimed primarily at practitioners, researches, and professionals in statistics, data mining, business intelligence, and systems engineering, but it is also accessible to graduate and undergraduate students in applied mathematics, computer science, electrical and process engineering. Familiarity with the basics of system identification and fuzzy systems is helpful but not required.

Key features:

- Detailed overview of the most powerful algorithms and approaches for data mining and system identification is presented.

- Extensive references give a good overview of the current state of the application of computational intelligence in data mining and system identification, and suggest further reading for additional research.

- Numerous illustrations to facilitate the understanding of ideas and methods presented.

- Supporting MATLAB files, available at the website create a computational platform for exploration and illustration of many concepts and algorithms presented in the book.



Spécifications produit

Contenu

Langue
en
Version
Couverture rigide
Date de sortie initiale
22 juin 2007
Nombre de pages
303
Illustrations
Non

Personnes impliquées

Auteur principal
Deuxième auteur
Coauteur
Editeur principal

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Autres spécifications

Hauteur de l'emballage
19 mm
Largeur d'emballage
165 mm
Largeur du produit
210 mm
Livre d‘étude
Non
Longueur d'emballage
229 mm
Longueur du produit
297 mm
Poids de l'emballage
748 g
Police de caractères extra large
Non
Édition
2007 ed.

EAN

EAN
9783764379872

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