Titlebook: Neural Networks and Soft Computing; Proceedings of the S Leszek Rutkowski,Janusz Kacprzyk Conference proceedings 2003 Physica-Verlag Heidel

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Soft Variables as a Generalization of Uncertain, Random and Fuzzy Variables uncertain variables, nonparametric decision problems based on uncertain, random and fuzzy variables are presented. The analogies lead to the formulation of so called soft variables described by evaluating functions, introduced as a tool for a unification and generalization of decision problems base

APEX

Decision Algorithms, Bayes’ Theorem and Flow Graphsithm reveals probabilistic properties, particularly it satisfies the total probability theorem and Bayes’ theorem. This leads to a new look on Bayesian inference methodology, showing that Bayes’ theorem can be used to reason directly from data without referring to prior and posterior probabilities,

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Interpolation in Hierarchical Rule Basesroblem in the special case of telecommunication supervision systems (TSS). Telecommunication networks are usually very large and complex, so the design of intelligent supervision systems raises the need of algorithms that can handle large amount of data, in high dimensional spaces in a user-friendly

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