Learning Systems: From Theory to Practice

By presenting the latest advances in fuzzy sets and computing with words from around the globe, this book disseminates recent innovations in advanced intelligent technologies and systems. From intelligent control and intuitionistic fuzzy quantifiers to various data science and industrial applications, it includes a wide range of valuable lessons learned and ideas for future intelligent products and systems.

From von Neumann architecture and Atanasoff’s ABC to Neuro-morphic Computation and Kasabov’s NeuCube: Principles and Implementations.- Applications of Computational Intelligence in Industrial and Environmental Scenarios.- Real, Imaginary and Complex Sets.- Intercriteria analysis over patterns.- From Primary to Conventional Science.- Intelligent Two-Level Optimization and Model Predictive Control of Degrading Plants.- Collaborative Clustering: New Perspective to Rank Factor Granules.- Learning through Contstraint Applications.- Autonomous Flight Control and Precise Gestural Positioning of a Small Quadrotor.- Introduction to the Theory of Randomized Machine Learning.- Grid-Type Fuzzy Models for Performance Evaluation and Condition Monitoring of Photovoltaic Systems.- Intelligent Control of Uncertain Switched Nonlinear Plants: NFG Optimum Control Synthesis via Switched Fuzzy Time-delay Systems.- Multidimensional Intuitionistic Fuzzy Quanti?ers and Level Operators.- Data Processing and Harmonization for Intelligent Transportation Systems. An Application Scenario on Highway Traffic Flows.