Innovations in Intelligent Systems / Edition 1by Ajith Abraham
Pub. Date: 02/15/2004
Publisher: Springer Berlin Heidelberg
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,
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.
Table of Contents
Use of multi-category proximal SVM for data set reduction.- Bayesian control of dynamic systems.- AppART: a hybrid neural network based on adaptive resonance theory for universal function approximation.- An algorithmic approach to the main concepts of rough set theory.- Automated case selection from databases using similarity-based rough approximation.- An induction algorithm with selection significance based on a fuzzy derivative.- Model and fixpoint semantics for fuzzy disjunctive programs with weak similarity.- An automated report generation tool for the data understanding phase.- Finding trigonometric identities with tree adjunct grammar guided genetic Modeling a distributed knowledge management for autonomous cooperative agents with knowledge migration programming.- Intelligent information systems based on paraconsistent logic programs.- Neuro-fuzzy paradigms for intelligent energy management.- Information space optimization for inductive learning.- Detecting, tracking, and classifying human movement using active contour Fuzzy sets in investigation of human cognition processes models and neural networks.- A full explanation facility for an MLP network that classifies .- Automatic translation to controlled medical vocabularies low-back-pain patients and for predicting MLP reliability.- A genetic programming for the induction of natural language parser.
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