Autonomous Learning Systems - From Data Streams to Knowledge in Real-time

Autor: Plamen Angelov

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Legare: Copertă tare

Editura: John Wiley and Sons Ltd

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Autonomous Learning Systems is the result of over a decade of focused research and studies in this...

Informații despre carte

Autor

Plamen Angelov

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2012

Pagini

298

EAN

9781119951520

ISBN

1119951526

Enbook ID

01250394

Editura

John Wiley and Sons Ltd

Greutate

604

Dimensiuni

252 x 176 x 15

Descriere completă

Autonomous Learning Systems is the result of over a decade of focused research and studies in this emerging area which spans a number of well-known and well-established disciplines that include machine learning, system identification, data mining, fuzzy logic, neural networks, neuro-fuzzy systems, control theory and pattern recognition. The evolution of these systems has been both industry-driven with an increasing demand from sectors such as defence and security, aerospace and advanced process industries, bio-medicine and intelligent transportation, as well as research-driven -- there is a strong trend of innovation of all of the above well-established research disciplines that is linked to their on-line and real-time application; their adaptability and flexibility. Providing an introduction to the key technologies, detailed technical explanations of the methodology, and an illustration of the practical relevance of the approach with a wide range of applications, this book addresses the challenges of autonomous learning systems with a systematic approach that lays the foundations for a fast growing area of research that will underpin a range of technological applications vital to both industry and society. Key features: Presents the subject systematically from explaining the fundamentals to illustrating the proposed approach with numerous applications. Covers a wide range of applications in fields including unmanned vehicles/robotics, oilrefineries, chemical industry, evolving user behaviour and activity recognition. Reviews traditional fields including clustering, classification, control, fault detection andanomaly detection, filtering and estimation through the prism of evolving and autonomously learning mechanisms. Accompanied by a website hosting additional material, including the software toolbox andlecture notes. Autonomous Learning Systems provides a 'one-stop shop' on the subject for academics, students, researchers and practicing engineers. It is also a valuable reference for Government agencies and software developers.

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Autonomous Learning Systems - From Data Streams to Knowledge in Real-time

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