Abstract

The purpose of the research is adaptation of biclasticization criteria, which have the properties of external complement to the problems of classification of states of complex technical objects in the field of computer engineering. The principles of inductive modelling of complex systems, in particular, the principle of external complementarity, as well as the methodology of the theory of pattern recognition, methods of inductive cluster analysis, mathematical statistics are applied. The construction of the criterion of stability of intra-multiple distances is based on the schemes of known criteria of self-organization of models, in particular the criterion of model inconsistencies, which are widely used in multi-step image recognition algorithms with intelligent choice of optimal results. The paper proposes the application of the criterion of stability of intra-multiple distances in the problems of diagnosing the state of technical objects, in particular, in the field of computer engineering. Since the application of such a criterion requires the presence of a target feature, one of the options for splitting the original experimental database into two subsets has been adapted: a subset of target features and a subset of input parameters. The concept of intra-multiple distances is extended to the application of algorithms of optimal complexity in the criteria of self-organization algorithms. Intelligent algorithms for self-organization of models of optimal complexity can be used to increase the reliability of computer systems.

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