Pattern Recognition and Classification in Time Series Data

Pattern Recognition and Classification in Time Series Data

Part of the Research Essentials Collection
Eva Volna, Martin Kotyrba, Michal Janosek
Indexed In: SCOPUS
Release Date: July, 2016|Copyright: © 2017 |Pages: 282
DOI: 10.4018/978-1-5225-0565-5
ISBN13: 9781522505655|ISBN10: 1522505652|EISBN13: 9781522505662
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Description & Coverage
Description:

Patterns can be any number of items that occur repeatedly, whether in the behaviour of animals, humans, traffic, or even in the appearance of a design. As technologies continue to advance, recognizing, mimicking, and responding to all types of patterns becomes more precise.

Pattern Recognition and Classification in Time Series Data focuses on intelligent methods and techniques for recognizing and storing dynamic patterns. Emphasizing topics related to artificial intelligence, pattern management, and algorithm development, in addition to practical examples and applications, this publication is an essential reference source for graduate students, researchers, and professionals in a variety of computer-related disciplines.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Algorithms
  • Automated Systems
  • Language Modelling
  • Optimization Methods
  • Pattern Management
  • Statistics
Reviews & Statements

Editors Volna, Kotyrba, and Janosek present readers with a collection of academic essays and scholarly articles focused on intelligent methods and techniques for recognizing and storing dynamic patterns. The eight selections that make up the main body of the text are devoted to the recognition of patterns with fractal structure in a time series, artificial intelligence algorithms for classification and pattern recognition, modeling and language support for pattern management, and a great many other related subjects.

– Protoview Reviews
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Editor/Author Biographies
Eva Volna is an associate professor at the Department of Computer Science at University of Ostrava, Czech Republic. Her interests include artificial intelligence, artificial neural networks, evolutionary algorithms, and cognitive science. She is an author of more than 50 papers in technical journals and proceedings of conferences.
Martin Kotyrba is an assistant professor at the Department of Computer Science at the University of Ostrava, Czech Republic. His interests include artificial intelligence, formal logic, soft computing methods and fractals. He is an author of more than 30 papers in conference proceedings.
Michal Janosek is an assistant professor at the Department of Informatics and Computers at the University of Ostrava, Czech Republic. His interests include artificial intelligence, multi-agent systems, modeling and simulations. He is an author of more than 20 papers in proceedings of conferences.
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