Information and Analytical System for Assessing Cognitive Functions of Aviation Personnel Based on Fuzzy Logic
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Abstract
The article presents an information and analytical system for assessing eight cognitive functions of aviation personnel based on fuzzy logic. The system receives 14 input variables, which are the results of subjects passing 13 validated psychodiagnostic methods. The system operates based on the Mamdani fuzzy inference algorithm, scalable to the input space dimension (1, 2 or 3 metrics) and using adaptive bases of production rules (3, 9 or 27). The generated quantitative assessments of eight cognitive functions in the range [0; 1] are fed to a three-level classifier, which implements their qualitative interpretation by assigning them to one of three zones: risk [0;0.4], acceptable level (0.4;0.7] or high level (0.7;1]. The practical significance of the developed information-analytical system lies in its role as a tool for automated decision support for professional selection specialists. Implementing the system will enable a shift from a binary «fit/unfit» assessment to a differentiated approach to managing personnel risks that takes into account the structure of a candidate's cognitive profile.
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References
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