Identification of the logical-and-probabilistic risk models of structurally complex systems with groups of inconsistent events

The theory of identification of the logical-and-probabilistic risk models of structurally complex systems with groups of inconsistent events was presented. For the logical-and-probabilistic risk models, their high precision and stability based on the groups of inconsistent events (Bayes formulas) and a well-organized risk polynomial was substantiated. Precision and stability of the logical-and-probabilistic risk models was compared with the well-known methods of classification of objects. For systems of various logical complexity, examples of identification and analysis of the logical-and-probabilistic models were presented.