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.
Reviews and Testimonials
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