Fuzzy Logic and Neural Networks Application in Estimation of Economic Security

Abstract

The paper presents the results of estimation of the level of economic security based on fuzzy logic and neural networks algorithms. The suggested model takes into account the fact of uncertainty of external and internal threats of enterprise economic security. The basis term set was determined as “absolute”, “satisfactory”, “unsatisfactory” and “critical”. The system of weights for initial indicators was estimated. The membership functions for each linguistic term from the initial term set were obtained. The proposed models make it possible to estimate the level of economic security, to analyze the current situation and to predict the future levels of economic security.