Development of the generic system of inference rules by knowledgebase

Abstract

The authors propose to align logical inference with the apparatus of fuzzy sets. When each solution is associated with a set of possible results with the known transitional probabilities, the solution is based on the digital information under uncertainty. Therefore, the main purpose of using fuzzy logic in expert systems consists in creation of computing devices (or software applications) that can imitate human-level reasoning and explain the techniques of decision-making. The goal of this research consists in detailed description of the reproducible standard method of setting rules of inference of the expert system for various economic subject fields, using a universal pattern of knowledgebase. For decision-making in a fuzzy system, the author suggests using the process of identification rule framework – determination of structural characteristics of fuzzy system, such as the number of fuzzy rules, number of linguistic terms the incoming variables are divided to. Such identification is conducted based on the fuzzy cluster analysis, using fuzzy decision trees. The authors present the structural chart of inference method on the basis of fuzzy logic. The presented in the article method of setting rules and fuzzy inference algorithm presented can be implemented in different areas of economics. The novelty of this work consists in automation and integration of the system for determination of fuzzy inference rules with the stage of input data collection in the subject field.