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Advances in Computational Intelligence Systems
Title statement Advances in Computational Intelligence Systems [electronic resource] : Contributions Presented at the 16th UK Workshop on Computational Intelligence, September 7–9, 2016, Lancaster, UK / edited by Plamen Angelov, Alexander Gegov, Chrisina Jayne, Qiang Shen. Publication Cham : Springer International Publishing : Imprint: Springer, 2017. Phys.des. IX, 508 p. 169 illus., 100 illus. in color. online resource. ISBN 9783319465623 Edition Advances in Intelligent Systems and Computing, ISSN 2194-5357 ; 513 Contents Search and Optimisation (SO) -- Modelling and Simulation (MS) -- Analysis and Detection (AD) -- Cognition and Control (CC) -- Learning and Evolution (LE) -- Clustering and Regression (CR). Notes to Availability Přístup pouze pro oprávněné uživatele Another responsib. Angelov, Plamen. Gegov, Alexander. Jayne, Chrisina. Shen, Qiang. Another responsib. SpringerLink (Online service) Subj. Headings Engineering. * Artificial intelligence. * Image processing. * Computational intelligence. * Control engineering. Form, Genre elektronické knihy electronic books Country Německo Language angličtina Document kind Electronic books URL Plný text pro studenty a zaměstnance UPOL 
book
The book is a timely report on advanced methods and applications of computational intelligence systems. It covers a long list of interconnected research areas, such as fuzzy systems, neural networks, evolutionary computation, evolving systems and machine learning. The individual chapters are based on peer-reviewed contributions presented at the 16th Annual UK Workshop on Computational Intelligence, held on September 7-9, 2016, in Lancaster, UK. The book puts a special emphasis on novels methods and reports on their use in a wide range of applications areas, thus providing both academics and professionals with a comprehensive and timely overview of new trends in computational intelligence.
Search and Optimisation (SO) -- Modelling and Simulation (MS) -- Analysis and Detection (AD) -- Cognition and Control (CC) -- Learning and Evolution (LE) -- Clustering and Regression (CR).
Number of the records: 1