Evolving Intelligent Systems Methodology and Applications
Aus der Reihe
IEEE Press Series on Computational Intelligence
134,99 €
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
Kopierschutz
Ja
Family Sharing
Nein
Text-to-Speech
Nein
Erscheinungsdatum
25.03.2010
Herausgeber
Plamen Angelov + weitereVerlag
John Wiley & SonsSeitenzahl
464 (Printausgabe)
Dateigröße
13243 KB
Auflage
1. Auflage
Sprache
Englisch
EAN
9780470569955
From theory to techniques, the first all-in-one resource for
EIS
There is a clear demand in advanced process industries, defense,
and Internet and communication (VoIP) applications for intelligent
yet adaptive/evolving systems. Evolving Intelligent Systems is the
first self- contained volume that covers this newly established
concept in its entirety, from a systematic methodology to case
studies to industrial applications. Featuring chapters written by
leading world experts, it addresses the progress, trends, and major
achievements in this emerging research field, with a strong
emphasis on the balance between novel theoretical results and
solutions and practical real-life applications.
* Explains the following fundamental approaches for developing
evolving intelligent systems (EIS):
* * the Hierarchical Prioritized Structure
* the Participatory Learning Paradigm
* the Evolving Takagi-Sugeno fuzzy systems (eTS+)
* the evolving clustering algorithm that stems from the well-known
Gustafson-Kessel offline clustering algorithm
* Emphasizes the importance and increased interest in online
processing of data streams
* Outlines the general strategy of using the fuzzy dynamic
clustering as a foundation for evolvable information
granulation
* Presents a methodology for developing robust and interpretable
evolving fuzzy rule-based systems
* Introduces an integrated approach to incremental (real-time)
feature extraction and classification
* Proposes a study on the stability of evolving neuro-fuzzy
recurrent networks
* Details methodologies for evolving clustering and
classification
* Reveals different applications of EIS to address real problems
in areas of:
* * evolving inferential sensors in chemical and petrochemical
industry
* learning and recognition in robotics
* Features downloadable software resources
Evolving Intelligent Systems is the one-stop reference guide for
both theoretical and practical issues for computer scientists,
engineers, researchers, applied mathematicians, machine learning
and data mining experts, graduate students, and professionals.
EIS
There is a clear demand in advanced process industries, defense,
and Internet and communication (VoIP) applications for intelligent
yet adaptive/evolving systems. Evolving Intelligent Systems is the
first self- contained volume that covers this newly established
concept in its entirety, from a systematic methodology to case
studies to industrial applications. Featuring chapters written by
leading world experts, it addresses the progress, trends, and major
achievements in this emerging research field, with a strong
emphasis on the balance between novel theoretical results and
solutions and practical real-life applications.
* Explains the following fundamental approaches for developing
evolving intelligent systems (EIS):
* * the Hierarchical Prioritized Structure
* the Participatory Learning Paradigm
* the Evolving Takagi-Sugeno fuzzy systems (eTS+)
* the evolving clustering algorithm that stems from the well-known
Gustafson-Kessel offline clustering algorithm
* Emphasizes the importance and increased interest in online
processing of data streams
* Outlines the general strategy of using the fuzzy dynamic
clustering as a foundation for evolvable information
granulation
* Presents a methodology for developing robust and interpretable
evolving fuzzy rule-based systems
* Introduces an integrated approach to incremental (real-time)
feature extraction and classification
* Proposes a study on the stability of evolving neuro-fuzzy
recurrent networks
* Details methodologies for evolving clustering and
classification
* Reveals different applications of EIS to address real problems
in areas of:
* * evolving inferential sensors in chemical and petrochemical
industry
* learning and recognition in robotics
* Features downloadable software resources
Evolving Intelligent Systems is the one-stop reference guide for
both theoretical and practical issues for computer scientists,
engineers, researchers, applied mathematicians, machine learning
and data mining experts, graduate students, and professionals.
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