Application of time series analysis for structural and parametric identification of fuzzy cognitive models

Abstract

The article deals with problems of structural and parametric identification of fuzzy cognitive models on the basis of statistical data analysis. The feasibility of application of time series analysis for solving these problems is justified. The Granger causality test is proposed for structural identification. An approach for parametric identification based on distributed-lag time series model is also proposed. The results of experimental verification of the described approaches are presented.