THE TECHNOLOGY OF FORMING FUZZY MODELS FOR ASSESSING THE STATE OF OBJECTS IN CONDITIONS OF UNCERTAINTY
The technology for the formation of fuzzy models for assessing the state of objects under the conditions of different types, fuzziness and incompleteness of the source data is proposed. The disadvantages of the traditional approach to the construction of fuzzy models in decision support systems are considered. To eliminate them, the feasibility of implementing a knowledge discovery strategy in databases is shown, taking into account the characteristics of the problem being solved. To assess the state of objects under conditions of uncertainty, a new type of fuzzy production rules is proposed. For their formation, an approach based on the training and testing of fuzzy neural networks was used. The results of testing the proposed technology showed its effectiveness and the possibility of practical use for the formation of fuzzy models for assessing the state of objects in various subject areas.