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Summary of Pattern Recognition and Classification in Time Series Data by Volna, Eva PDF

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.

Pattern Recognition and Classification in Time Series Data

Detail About Pattern Recognition and Classification in Time Series Data PDF

  • Author : Volna, Eva
  • Publisher : IGI Global
  • Genre : Computers
  • Total Pages : 282 pages
  • ISBN : 1522505660
  • PDF File Size : 51,5 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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  • Publisher : World Scientific
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Comprising papers presented at an international symposium on fuzzy engineering technology, this volume provides information on the current state-of-the-art in the field of fuzzy theories and applications, and their importance

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This book constitutes the refereed proceedings of the 34th Symposium of the German Association for Pattern Recognition, DAGM 2012, and the 36th Symposium of the Austrian Association for Pattern Recognition, OAGM 2012,

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  • File Size : 20,8 Mb
  • Release Date : 30 August 2018
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Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and

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  • File Size : 26,9 Mb
  • Release Date : 25 July 2014
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Comprehensive Coverage of the Entire Area of Classification Research on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning.

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  • File Size : 22,7 Mb
  • Release Date : 06 November 2019
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This book aims to provide readers with the current information, developments, and trends in a time series analysis, particularly in time series data patterns, technical methodologies, and real-world applications. This

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  • File Size : 41,8 Mb
  • Release Date : 18 August 2005
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The two volume set LNCS 3686 and LNCS 3687 constitutes the refereed proceedings of the Third International Conference on Advances in Pattern Recognition, ICAPR 2005, held in Bath, UK in August 2005. The papers