Artificial orthogonalization of a passive experiment for a small sample of fuzzy data for constructing regression equations

Technology for constructing models of functioning systems under uncertainty

Development of a procedure for estimating regression equation parameters for a sample of fuzzy data

Artificial orthogonalization of a passive experiment for a small sample of fuzzy data for constructing regression equations

mathematical model, passive experiment, artificial orthogonalization, truncated orthogonal design, compactness of the uncertainty body, membership function, fuzzy value of the regression coefficient

The problem related to constructing regressions for a small sample under uncertainty of the response function estimated is solved. The problem is solved if the measured values of the function are taken as fuzzy numbers with known membership functions

Development of materials, technologies, diagnostics in engineering, medicine, economics, forecasting of economic and social systems under uncertainty

Input variables must be deterministic, the membership functions of the fuzzy value of the response function are given in Gaussian form