Knowledge-Based Intelligent System Advancements: Systemic and Cybernetic Approaches: Systemic and Cybernetic Approaches

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Jozefczyk, Jerzy
IGI Global, 31. aug 2010 - 506 pages
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The integration of artificial intelligence and knowledge based methods and technologies as well as computer based information systems has created the next generation of information systems – intelligent information systems. This connection enables these new information systems to demonstrate novel capabilities, in particular: supporting users in decision making, processing data, discovering and processing knowledge, and reasoning under uncertainty.

Knowledge-Based Intelligent System Advancements: Systemic and Cybernetic Approaches presents selected new AI–based ideas and methods for analysis and decision making in intelligent information systems derived using systemic and cybernetic approaches. This book is useful for researchers, practitioners and students interested intelligent information retrieval and processing, machine learning and adaptation, knowledge discovery, applications of fuzzy based methods and neural networks.

 

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Contents

Stochastic LearningBased WeakEstimation and its Applications
1
On Analogue TMR System
30
Application of TwoStage Adaptive DecisionMaking System Based onTakagiSugeno Modelfor Scenario Selection inRehabilitation Process
47
Probabilistic TemporalNetwork for Numeric andSymbolic Time Information
67
Object Recognition via ContourPoints Reconstruction UsingHurwitzRadon Matrices
87
Fuzzy Logic BasedModeling in the ComplexSystem Fault Diagnosis
108
Towards Knowledge DrivenIndividual IntegratedIndicators of Innovativeness
129
Knowledge Exchange inCollaborative Networksof Enterprises
141
Knowledge RedundancyEnvironmental Shocks andAgents Opportunism
252
Perspectives of MultivariableFuzzy Control
283
A Review of Developments
315
Active Learning in DiscreteTime Stochastic Systems
350
Hybrid Intelligent DiagnosisApproach Based on NeuralPattern Recognition andFuzzy DecisionMaking
372
Nonlinear Adaptive ShipControl Synthesis In TheCase Of Model Uncertainty
395
A KnowledgeBasedApproach for MicrowireCasting Plant Control
419
Compilation of References
438

A New MetaHeuristic MultiObjective Approach for OptimalDispatch of Dispersed andRenewable Generating Units inPower Distribution Systems
162
Output Stream of BindingNeuron with Feedback
182
Expert Guided AutonomousMobile Robot Learning
216
Validation of ClusteringTechniques for StudentGrouping in IntelligentElearning Systems
232

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About the author (2010)

Jerzy Józefczyk graduated in automatic control systems from the Wroclaw University of Technology, in 1980. He received the Ph.D. degree in computer science from the Poznan University of Technology, in 1987, and Dr. Sc. degree in automation and robotics from the Systems Research Institute of the Polish Academy of Sciences, Warsaw, in 1996. Presently, he is a full professor in the Wroclaw University of Technology, and a head of the Department of Intelligent Decision Making Systems. His research interests include operations research, complex control systems, uncertain systems and artificial intelligence which resulted in more than 100 publications. He was a Scientific Secretary of the Committee of Automation and Robotics of the Polish Academy of Sciences in 1988–2006 and a member of this Committee from 1988. He is currently a member of a Board of Directors of the World Organisation of Systems and Cybernetics.

Donat Orski received M.Sc. and Ph.D. degrees in computer science from the Wroclaw University of Technology (WUT), in 1995 and 2000, respectively. Currently, he is an assistant professor in the Department of Intelligent Decision Making Systems in WUT. His research interests include knowledge-based systems, expert systems, uncertain systems, neural networks, learning systems, and their applications to decision making in complex operation systems. He is an author or co-author of more than 30 conference papers, journal articles and book chapters on these topics. [Editor]

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