Application of Fuzzy Comprehensive Evaluation Based on Genetic Algorithm in Psychological Measurement

Abstract

Fuzzy comprehensive evaluation (FCE) is an artificial evaluation technique based on fuzzy mathematics, with real and accurate evaluation results that are extensively utilized in psychology and other fields. Hence, a technique is needed for assessing Likert scale data using fuzzy mathematics. This study examines the operators and weight distribution of the variables while individuals perform a complete and comprehensive evaluation and apply a genetic algorithm (GA) to determine the corresponding weight. Genetic processes based on population adaptation and evolution fundamentals have been hugely successful in solving problems and producing optimal solutions a long time ago. Furthermore, we measure psychological data from the Likert scale and analyze it using a fluid-based GA for a complete psychological assessment. Students of various genders used different compound operators and weight distribution to evaluate the instant noodle completely. This reflects the fact that the employment of a GA-based fuzzy comprehensive evaluation in psychological measurement and consumer psychology study is beneficial. The results show that the fuzzy comprehensive evaluation method based on the GA can effectively analyze the psychological measurement data of the Likert scale.