Computational Complexity of the Accessory Function Setting Mechanism in Fuzzy Intellectual Systems

This article proposes a mechanism for processing fuzzy symptoms, as well as all related factors presented in natural language, which made it possible to improve the intellectual decision-making system in the field of cardiology by adjusting membership functions. The computational complexity of solving the problem according to the criterion of time costs is determined, it is close to exponential from the selected calculation accuracy, which indicates the effectiveness and the absence of disadvantages of the proposed mechanism for a given criterion. The software implementation of the mechanism for setting membership functions in a fuzzy intellectual system is implemented in the Python 3.6 object-oriented programming environment. The laboratory operation of a fuzzy intellectual system has confirmed the high reliability of making objective decisions in the medical subject area.