IMCS/Publications/CSJM/Issues/CSJM v.9, n.3 (27), 2001/

Genetic algorithms for the synthesis optimization of a set of irredundant diagnostic tests in the intelligent system

Authors: Anna E.Yankovskaya, Alex M. Bleikher


Method of the synthesis optimization of a set of irredundant diagnostic tests with genetic algorithms used to solve problems of large dimension is suggested. The idea of creating the irredundant partial implication matrix sectionalized by classification mechanisms lies in the base; creating a set of irredundant diagnostic tests is based on revealing certain kinds of regularities with the use of genetic transformations. All the obligatory and non-informative features are not used in genetic transformations. Procedures of selection able-to-compete individuals from populations, decision making concerning the object under examination of each able-to-compete individual from populations, and organizing of voting on the set of these individuals are suggested. In order to solve these problems the intelligent system is used.

A.E. Yankovskaya, Alex M. Bleikher,
Anna E. Yankovskaya,
Tomsk State University of Architecture and Building,
2 Solyanaya square, 634003,
Tomsk, Russia
Phone: +7(3822) 656924
Alex M. Bleikher
Tomsk Polytechnic University,
30, Lenin avenue, 634034,
Tomsk, Russia
Phone: +7(3822) 418227


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