Adam E Gaw?da; Janusz Kacprzyk; Leszek Rutkowski; Advances in Data Analysis with Computational Intelligence Methods 9783319885162

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Автор: Adam E Gaw?da; Janusz Kacprzyk; Leszek Rutkowski;
Название: Advances in Data Analysis with Computational Intelligence Methods
ISBN: 9783319885162
Издательство: Springer
Классификация:

Прикладная математика

Искусственный интеллект

ISBN-10: 3319885162
Обложка/Формат: Soft cover
Страницы: 412
Вес: 0.66 кг.
Дата издания: 2018
Серия: Studies in Computational Intelligence
Язык: English
Издание: Softcover reprint of
Иллюстрации: 59 illustrations, color; 67 illustrations, black and white; xx, 412 p. 126 illus., 59 illus. in color.
Размер: Book (Paperback Initiative)
Читательская аудитория: Professional & vocational
Основная тема: Engineering
Подзаголовок: Dedicated to Professor Jacek ?urada
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: This book is a tribute to Professor Jacek ?urada, who is best known for his contributions to computational intelligence and knowledge-based neurocomputing. It is dedicated to Professor Jacek ?urada, 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 ?urada’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.

Дополнительное описание: PART 1, Data mining, machine learning, knowledge discovery, Tensor Networks for Dimensionality Reduction, Big Data and Deep Learning.- Local Data Characteristics in Learning Classifiers from Imbalanced Data.- Similarity dimensions of semantic ontologies.-

Advances in Data Analysis with Computational Intelligence Methods, Adam E Gaw?da; Janusz Kacprzyk; Leszek Rutkowski;