PROCEEDINGS IPMU '08
Inverse Problem Solving based on IF-THEN Rules and Genetic Algorithms
Alexander P. Rotshtein, Hanna B. Rakytyanska.
This paper proposes an approach for
inverse problem solving based on the
description of the interconnection
between unobserved and observed
parameters of an object with the
help of fuzzy IF-THEN rules. The
essence of the approach proposed
consists in formulating and solving
the optim-ization problems, which,
on the one hand, find the roots of
fuzzy logical equations,
corresponding to IF-THEN rules,
and on the other hand, tune the
fuzzy model on the readily available
experimental data. The genetic
algorithms are proposed for the
optimization problems solving.
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