Advances in Data Analysis with Computational Intelligence Methods

Advances in Data Analysis with Computational Intelligence Methods
Author :
Publisher : Springer
Total Pages : 417
Release :
ISBN-10 : 9783319679464
ISBN-13 : 3319679465
Rating : 4/5 (64 Downloads)

Book Synopsis Advances in Data Analysis with Computational Intelligence Methods by : Adam E Gawęda

Download or read book Advances in Data Analysis with Computational Intelligence Methods written by Adam E Gawęda and published by Springer. This book was released on 2017-09-21 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a tribute to Professor Jacek Żurada, who is best known for his contributions to computational intelligence and knowledge-based neurocomputing. It is dedicated to Professor Jacek Żurada, Full Professor at the Computational Intelligence Laboratory, Department of Electrical and Computer Engineering, J.B. Speed School of Engineering, University of Louisville, Kentucky, USA, as a token of appreciation for his scientific and scholarly achievements, and for his longstanding service to many communities, notably the computational intelligence community, in particular neural networks, machine learning, data analyses and data mining, but also the fuzzy logic and evolutionary computation communities, to name but a few. At the same time, the book recognizes and honors Professor Żurada’s dedication and service to many scientific, scholarly and professional societies, especially the IEEE (Institute of Electrical and Electronics Engineers), the world’s largest professional technical professional organization dedicated to advancing science and technology in a broad spectrum of areas and fields. The volume is divided into five major parts, the first of which addresses theoretic, algorithmic and implementation problems related to the intelligent use of data in the sense of how to derive practically useful information and knowledge from data. In turn, Part 2 is devoted to various aspects of neural networks and connectionist systems. Part 3 deals with essential tools and techniques for intelligent technologies in systems modeling and Part 4 focuses on intelligent technologies in decision-making, optimization and control, while Part 5 explores the applications of intelligent technologies.


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