Téléchargez le livre : Learning in Non-Stationary Environments

Learning in Non-Stationary Environments

Methods and Applications de

,

Éditeur :

Springer


Paru le : 2012-04-13

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Description

Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers. The result is significant increases in system complexity and state changes, information sources, the need for faster data handling and the integration of environmental influences. Intelligent systems, equipped with a taxonomy of data-driven system identification and machine learning algorithms, can handle these problems partially. Conventional learning algorithms in a batch off-line setting fail whenever dynamic changes of the process appear due to non-stationary environments and external influences.
 
Learning in Non-Stationary Environments: Methods and Applications offers a wide-ranging, comprehensive review of recent developments and important methodologies in the field. The coverage focuses on dynamic learning in unsupervised problems, dynamic learning in supervised classification and dynamic learning in supervised regression problems. A later section is dedicated to applications in which dynamic learning methods serve as keystones for achieving models with high accuracy.
 
Rather than rely on a mathematical theorem/proof style, the editors highlight numerous figures, tables, examples and applications, together with their explanations.
 
This approach offers a useful basis for further investigation and fresh ideas and motivates and inspires newcomers to explore this promising and still emerging field of research.
 
Pages
440 pages
Collection
n.c
Parution
2012-04-13
Marque
Springer
EAN papier
9781441980199
EAN EPUB
9781441980205
Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
44
Taille du fichier
15995 Ko
Prix
147,69 €

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