Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Application of Uncertain Variables to Decision Making in a Class of Distributed Computer Systems
Proceedings of the IFIP 17th World Computer Congress - TC12 Stream on Intelligent Information Processing
New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing (Studies in Fuzziness and Soft Computing, V. 143)
Analysis and Decision Making in Uncertain Systems (COMMUNICATIONS AND CONTROL ENGINEERING)
Analysis and Decision Making in Uncertain Systems (COMMUNICATIONS AND CONTROL ENGINEERING)
Modern Control Theory
Uncertain variables and their application to decision making problems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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The uncertain variables have been introduced and developed as a tool for analysis and decision making in a class of uncertain systems described by traditional mathematical models or by relational knowledge representations with unknown parameters characterized by an expert. The purpose of this paper is to show how the uncertain variables may be applied to decision making in a class of uncertain systems with the cascade structure consisting of parts (elements) with different descriptions of the uncertainty. The different cases have been considered: the random and uncertain parameters in the different parts of the system and the random parameter in the certainty distribution. The first part of the paper presents a general approach to decision making in the complex system consisting of elements with random parameters and elements with uncertain parameters treated as values of uncertain variables characterized by certainty distributions given by an expert. The second part is devoted to a special case: the system with a cascade structure containing random and uncertain parts. The first subsystem is described by probability distribution and the second subsystem is characterized by an expert. Simple numerical examples illustrate the presented problem and results. The description of he simulations and possibilities of practical applications for control of complex production systems are included.