RELATIONAL-SEPARABLE MODELS OF MONITORING PROCESSES WITH VARIABLE AND FUZZY OBSERVATION INTERVALS

Abstract

The report presents the results of research on the formation of models and procedures intended for the analysis and forecasting of the characteristics of non-deterministic processes represented by time sequences with uneven and fuzzy interval models (UFMI) between observations. At the same time, the data of monitoring processes of rehabilitation of patients, maintenance of systems according to the current state, etc. were used. at UFMI. The development of fuzzy relational and combined relational-separable models (RSM) of the first and second order, intended for the analysis and forecasting of sequences of UFMI data, was carried out. The possibility of increasing the accuracy and numerical efficiency of the modeling of the specified monitoring processes when applying RSM algorithms has been established.