Advertisement

Learning from Data Streams in Dynamic Environments

  • Moamar Sayed-Mouchaweh

Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Moamar Sayed-Mouchaweh
    Pages 1-10
  3. Moamar Sayed-Mouchaweh
    Pages 11-32
  4. Moamar Sayed-Mouchaweh
    Pages 33-59
  5. Moamar Sayed-Mouchaweh
    Pages 61-69
  6. Back Matter
    Pages 71-75

About this book

Introduction

This book addresses the problems of modeling, prediction, classification, data understanding and processing in non-stationary and unpredictable environments. It presents major and well-known methods and approaches for the design of systems able to learn and to fully adapt its structure and to adjust its parameters according to the changes in their environments. Also presents the problem of learning in non-stationary environments, its interests, its applications and challenges and studies the complementarities and the links between the different methods and techniques of learning in evolving and non-stationary environments.

Keywords

Adaptive Modeling Data Streams Drift Monitoring and Handling Evolving Systems Incremental Learning Non-stationary Environments Online Learning

Authors and affiliations

  • Moamar Sayed-Mouchaweh
    • 1
  1. 1.Computer Science and Automatic ControlHigh National Engineering School of Mine Computer Science and Automatic ControlDouaiFrance

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-25667-2
  • Copyright Information The Author 2016
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-25665-8
  • Online ISBN 978-3-319-25667-2
  • Series Print ISSN 2191-530X
  • Series Online ISSN 2191-5318
  • Buy this book on publisher's site
Industry Sectors
Pharma
Automotive
Chemical Manufacturing
Biotechnology
Finance, Business & Banking
Electronics
IT & Software
Telecommunications
Energy, Utilities & Environment
Aerospace
Oil, Gas & Geosciences
Engineering