Advances in Data Analysis with Computational Intelligence Methods

Book Description

This book is a tribute to Professor Jacek Żurada, who is best known for his contributions to computational and knowledge-based neurocomputing. It is dedicated to Professor Jacek Żurada, Full Professor at the Computational 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 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 Engineers), the world’s largest professional technical professional organization dedicated to advancing science and 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.

Table of Contents

Part 1 Data Mining, Machine Learning, Knowledge Discovery
Chapter 1 Tensor Networks For Dimensionality Reduction, Big Data And Deep Learning
Chapter 2 Local Data Characteristics In Learning Classifiers From Imbalanced Data
Chapter 3 Dimensions Of Semantic Similarity
Chapter 4 Some Interesting Phenomenon Occurring During Self-Learning Process With Its Psychological Interpretation

Part 2 Neural Networks And Connectionist Systems
Chapter 5 On The Interpretation And Characterization Of Echo State Networks Dynamics: A Complex Systems Perspective
Chapter 6 Optimization Of Ensemble Neural Networks With Type-1 And Interval Type-2 Fuzzy Integration For Forecasting The Taiwan Stock Exchange
Chapter 7 Deep Neural Networks—A Brief History

Part 3 Intelligent Technologies In Systems Modeling
Chapter 8 Techniques For And Integration Of Rule Bases
Chapter 9 New Aspects Of Interpretability Of Fuzzy Systems For Nonlinear Modeling
Chapter 10 On The Intuitionistic Fuzzy Sets Of N-Th Type

Part 4 Intelligent Technologies In Decision Making, Optimization And Control
Chapter 11 Mcts/Uct In Solving Real-Life Problems
Chapter 12 Interactive Cone Contraction For Evolutionary Mutliple Objective Optimization
Chapter 13 A Review Of Fuzzy And Mathematic Methods For Dynamic Parameter Adaptation In The Firefly Algorithm

Part 5 Applications Of Intelligent Technologies
Chapter 14 Computational Intelligence Methods In Personalized Pharmacotherapy
Chapter 15 Embodying Intelligence In Autonomous And Robotic Systems With The Use Of Cognitive Psychology And Motivation Theories
Chapter 16 Evolutionary Approach For Automatic Of Pid Controllers
Chapter 17 Fuzzy-Genetic Approach To Identity Verification Using A Handwritten Signature
Chapter 18 A Method Of Design And Optimization For Sic-Based Grid-Connected Ac-Dc Converters

Book Details

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