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Abstract
The decision-making algorithm selection is one of the problems that modern economics, industrial management and situation identification process face. The Bayesian composite approach is considered to be the safest way for algorithm identification. However, the approach based on Bayesian composite rules is time-consuming and computationally intensive, that`s why it is important to develop the method, when combined with the Bayesian approach, will enable to scale back the computation. The article describes the synthesis method of flow graphs for optimal search within the member group (including the search within the industrial structure) and suggests this method as the main implementable algorithm for situation identification, based on Bayesian composite rule for decision-making. Such scientific methods as mathematical techniques of graph theory, algorithm and combination methods, probability theory method, and methods of statistical analysis were used in the research.
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