Building a standard system of inference rules based on the knowledge base - Kopyrin, Andrey Sergeevich; Kopyrina, Alina Olegovna (Программные системы и вычислительные методы, 2021)
The authors propose to combine logical inference with the apparatus of fuzzy sets. When each solution is associated with a set of possible outcomes with known conditional probabilities, the solution is chosen based on digital information under conditions of uncertainty. Therefore, the main purpose of using fuzzy logic in expert systems is to create computing devices (or software complexes) capable of simulating human thinking and explaining decision-making methods The purpose of the work is to describe in detail a reproducible standard method of constructing rules for the output of an expert system for various economic subject areas, using a universal knowledge base scheme To make decisions in a fuzzy system, it is proposed to use the process of identifying the structure of a rule - determining the structural characteristics of a fuzzy system, such as the number of fuzzy rules, the number of linguistic terms into which incoming variables are divided. This identification is carried out using fuzzy cluster analysis, which is carried out using fuzzy decision trees. The authors present a block diagram of the inference methodology based on fuzzy logic. The method of constructing rules and the algorithm of fuzzy inference presented in the article can be used in various spheres of the economy. The novelty of the work lies in the automation and integration of the system for determining fuzzy inference rules with the stage of collecting input data in the subject area