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

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Published: 24-07-2021

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The object of research is

Technology for constructing models of functioning systems under uncertainty

The aim of research is to

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

Paper title

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

Keywords

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

Main scientific results imply the following

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

Scope of application

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

Limitations for practical use

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

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