A Diagnostic Method for Sleep Disorders Based on Multi-Attribute Group Decision Making

Abstract

This invention provides a sleep disorder diagnosis method based on multi-attribute group decision-making, comprising: acquiring evaluation information from multiple decision-makers regarding multiple alternatives under different attributes; constructing a decision matrix; determining the weights of each attribute using the entropy weight method; aggregating the evaluation information of each alternative under all attributes using an aggregation operator to obtain a comprehensive evaluation value for each alternative corresponding to each decision-maker; calculating the score of the comprehensive evaluation value; and obtaining the final score by weighting the scores based on the decision-maker's weight and then ranking them. This invention further proposes a distance metric method for fuzzy sets based on dual hesitant q-rung order that does not require standardization constraints and preserves the original data distribution. Furthermore, it objectively derives the entropy weight mechanism of weights through information entropy analysis, ensuring the integrity of the measurement and the objectivity of the decision in sleep disorder diagnosis.

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