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A Multi-Granularity Triangular Fuzzy Approach for Diabetes Blood Glucometer Selection Using PROMETHEE and Three-Way Decision
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Author(s): Liyin Wang (Shanxi University, China), Yuting Cheng (Shanxi University, China), Xueqing Fan (Shanxi University, China), Anna Wang (Shanxi University, China)and Hansen Zhao (Georgia Institute of Technology, USA)
Copyright: 2024
Pages: 21
Source title:
Big Data Quantification for Complex Decision-Making
Source Author(s)/Editor(s): Chao Zhang (Shanxi University, China)and Wentao Li (Southwest University, China)
DOI: 10.4018/979-8-3693-1582-8.ch002
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Abstract
This chapter focuses on the issue of selecting a blood glucose meter for diabetic patients. To address this problem, the authors have developed a comprehensive evaluation model that combines triangular fuzzy (TF) logic, multi-granularity (MG), three-way decision (TWD), and rough set theory. The evaluation model takes into consideration the performance indicators of the blood glucose meter and user requirements. The authors utilize TF logic to model the indicators and determine their weights, while integrating the TWD method to handle incomplete and uncertain information. Subsequently, they introduce the PROMETHEE method to comprehensively evaluate and rank various alternatives. Finally, within this evaluation model, they select the optimal choice based on its score. Experimental results demonstrate the effectiveness of our proposed method in resolving the blood glucose meter selection problem and providing personalized recommendations for diabetic patients.
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