Innovations in Intelligent Systems is a rare collection of the latest developments in intelligent paradigms such as knowledge-based systems, computational intelligence and hybrid combinations as well as practical applications in engineering, science, business and commerce. The book covers central topics such as intelligent multi-agent systems, data mining, case-based reasoning, and rough sets. Essential techniques to the development of intelligent machines are investigated such as pattern recognition and classification, machine learning, natural language processing, grammar, evolutionary schemes, fuzzy-neural procedures, and intelligent vision. The book also includes useful applications ranging from medical diagnosis and technical/medical language translation, to power demand forecasting and manufacturing plants. Due to its depth and breadth of the coverage and the usefulness of the techniques and applications, this book is a valuable reference for experts and students alike.

Latest developments in intelligent paradigms and practical interesting applications State of the art in building 'thinking' machines and improving our understanding of intelligence

Autorentext
Dr. Ajith Abraham is Director of the Machine Intelligence Research (MIR) Labs, a global network of research laboratories with headquarters near Seattle, WA, USA. He is an author/co-author of more than 750 scientific publications. He is founding Chair of the International Conference of Computational Aspects of Social Networks (CASoN), Chair of IEEE Systems Man and Cybernetics Society Technical Committee on Soft Computing (since 2008), and a Distinguished Lecturer of the IEEE Computer Society representing Europe (since 2011).

Inhalt
1 Theory.- 1. Use of multi-category proximal SVM for data set reduction.- 2. Bayesian control of dynamic systems.- 3. AppART: a hybrid neural network based on adaptive resonance theory for universal function approximation.- 4. An algorithmic approach to the main concepts of rough set theory.- 5. Automated case selection from databases using similarity-based rough approximation.- 6. An induction algorithm with selection significance based on a fuzzy derivative.- 7. Model and fixpoint semantics for fuzzy disjunctive programs with weak similarity.- 8. An automated report generation tool for the data understanding phase.- 9. Finding trigonometric identities with tree adjunct grammar guided genetic programming.- 2 Applications.- 10. Modeling a distributed knowledge management for autonomous cooperative agents with knowledge migration.- 11. Intelligent information systems based on paraconsistent logic programs.- 12. Neuro-fuzzy paradigms for intelligent energy management.- 13. Information space optimization for inductive learning.- 14. Detecting, tracking, and classifying human movement using active contour models and neural networks.- 15. Fuzzy sets in investigation of human cognition processes.- 16. A full explanation facility for an MLP network that classifies low-back-pain patients and for predicting MLP reliability.- 17. Automatic translation to controlled medical vocabularies.- 18. A genetic programming for the induction of natural language parser.- List of contributors.