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Learning in Non-Stationary Environments

Name: Learning in Non-Stationary Environments
Brand: Springer-Verlag New York Inc.
SKU: 9781441980199
Price: 824.13 RON
Availability: InStock

Methods and Applications

Autor: Moamar Sayed-Mouchaweh, Edwin Lughofer

Limbă:

Legare: Copertă tare

Editura: Springer-Verlag New York Inc.

Disponibilitate: În depozitul extern

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Recent decades have seen rapid advances in automatization processes, supported by modern machines an...

Informații despre carte

Autor

Moamar Sayed-Mouchaweh, Edwin Lughofer

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2012

Pagini

440

EAN

9781441980199

ISBN

1441980199

Enbook ID

01424348

Editura

Springer-Verlag New York Inc.

Greutate

840

Dimensiuni

155 x 235 x 27

Descriere completă

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.§