M. Ameer, Walid Emam, Awais Yousaf, Muhammad Younis
{"title":"Selection of Optimized Diagnostic Approach for Cardiovascular Diseases Leveraging Dynamic Linguistic Intuitionistic Fuzzy Decision-Making Technique","authors":"M. Ameer, Walid Emam, Awais Yousaf, Muhammad Younis","doi":"10.1002/eng2.70038","DOIUrl":null,"url":null,"abstract":"<p>Fuzzy mathematical operations play an important role in the field of decision-making. Decision-making tools are being used in every field of life. Fuzzy operators are the building blocks for making a decision in the realm of uncertain information. The information is often in qualitative form which needs a qualitative approach for decision-making rather than a quantitative one. The linguistic term sets are the mathematical tools to collect the qualitative data from experts of the fields and the conversion of linguistic data in the form linguistic intuitionistic fuzzy data is the more efficient and reliable for the process of decision making. The fuzzy aggregation operators are the best tools for the aggregation of uncertain and vague data. This work addresses a real-world decision-making problem of choosing the best diagnostic approach for the diagnosis of cardiovascular diseases by introducing a novel decision-making technique with fuzzy aggregation operators in the domain of linguistic intuitionistic fuzzy (LIF) sets. Two new operators are used in this method: the Dynamic Linguistic Intuitionistic Fuzzy Dombi Weighted Averaging (DLIFDWA) operator and the Dynamic Linguistic Intuitionistic Fuzzy Dombi Weighted Geometric (DLIFDWG) operator. This work aims to identify an optimal technique for diagnosing cardiovascular illness using Dombi operations in the Linguistic Intuitionistic Fuzzy environment. The Dombi Operations are highly versatile and successful in addressing vagueness and uncertainty, making them crucial in our methodology. To demonstrate the effectiveness of the offered strategies, we have implemented the recommended operators for the selection of optimized diagnostic approach for cardiovascular diseases. This showcases the significance of these strategies in facilitating decision-making. Ultimately, we perform a thorough analysis to showcase the reliability and uniformity of the produced procedures, comparing the provided operators with various current counterparts.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":"7 2","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.70038","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering reports : open access","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/eng2.70038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Fuzzy mathematical operations play an important role in the field of decision-making. Decision-making tools are being used in every field of life. Fuzzy operators are the building blocks for making a decision in the realm of uncertain information. The information is often in qualitative form which needs a qualitative approach for decision-making rather than a quantitative one. The linguistic term sets are the mathematical tools to collect the qualitative data from experts of the fields and the conversion of linguistic data in the form linguistic intuitionistic fuzzy data is the more efficient and reliable for the process of decision making. The fuzzy aggregation operators are the best tools for the aggregation of uncertain and vague data. This work addresses a real-world decision-making problem of choosing the best diagnostic approach for the diagnosis of cardiovascular diseases by introducing a novel decision-making technique with fuzzy aggregation operators in the domain of linguistic intuitionistic fuzzy (LIF) sets. Two new operators are used in this method: the Dynamic Linguistic Intuitionistic Fuzzy Dombi Weighted Averaging (DLIFDWA) operator and the Dynamic Linguistic Intuitionistic Fuzzy Dombi Weighted Geometric (DLIFDWG) operator. This work aims to identify an optimal technique for diagnosing cardiovascular illness using Dombi operations in the Linguistic Intuitionistic Fuzzy environment. The Dombi Operations are highly versatile and successful in addressing vagueness and uncertainty, making them crucial in our methodology. To demonstrate the effectiveness of the offered strategies, we have implemented the recommended operators for the selection of optimized diagnostic approach for cardiovascular diseases. This showcases the significance of these strategies in facilitating decision-making. Ultimately, we perform a thorough analysis to showcase the reliability and uniformity of the produced procedures, comparing the provided operators with various current counterparts.