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双极线性丢番图模糊超软集下基于爱因斯坦聚合算子的多准则决策方法

An MCDM approach on Einstein aggregation operators under Bipolar Linear Diophantine Fuzzy Hypersoft Set.

作者信息

Nithya Sri S, Vimala J, Kausar Nasreen, Ozbilge Ebru, Özbilge Emre, Pamucar Dragan

机构信息

Department of Mathematics, Alagappa University, Karaikudi, Tamilnadu, India.

Department of Mathematics, Faculty of Arts and Science, Yildiz Technical University, Esenler, 34220, Istanbul, Turkey.

出版信息

Heliyon. 2024 Apr 22;10(9):e29863. doi: 10.1016/j.heliyon.2024.e29863. eCollection 2024 May 15.

DOI:10.1016/j.heliyon.2024.e29863
PMID:39669370
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11636903/
Abstract

The most extended form of a fuzzy set called the Bipolar Linear Diophantine Fuzzy Hypersoft Set is implemented with some basic operations. This is an extraordinary technique for handling uncertainty because it has a choice of reference parameters with auxiliary attributes. A widely used operator named Einstein aggregation operators was developed in our proposed context. This new operator will make the decision-making method consistent with advancements in our priorities. The prolongation of this advanced operator helps solve critical data in real life. Cancer is a common and challenging disease that is growing day by day, with the proliferation of cells uncontrollably. It often grows tumors along with a tendency to disseminate to many different regions of the body. Lung Carcinoma(Lung Cancer) is the most common and dangerous type and is comprehensively explored in this study. By considering different stages, traits, and a multitude of complications, the investigation vigilantly focuses on several facets of lung carcinoma. The best therapy to overcome this problem is concluded by incorporating our established Bipolar Linear Diophantine Fuzzy Weighted Aggregation Operators. In spite of researching the problem from the healthcare perspective, the analysis delves into innovative ways for bettering the outcomes from therapies.

摘要

一种被称为双极线性丢番图模糊超软集的模糊集的最扩展形式是通过一些基本运算实现的。这是一种处理不确定性的非凡技术,因为它可以选择带有辅助属性的参考参数。在我们提出的背景下开发了一种广泛使用的算子,即爱因斯坦聚合算子。这个新算子将使决策方法与我们优先事项的进展保持一致。这种先进算子的扩展有助于解决现实生活中的关键数据。癌症是一种常见且具有挑战性的疾病,它随着细胞的不受控制增殖而日益增长。它经常会生长肿瘤,并且有扩散到身体许多不同部位的倾向。肺癌是最常见和最危险的类型,本研究对其进行了全面探讨。通过考虑不同阶段、特征和众多并发症,该调查密切关注肺癌的几个方面。通过纳入我们已建立的双极线性丢番图模糊加权聚合算子,得出了克服这一问题的最佳疗法。尽管从医疗保健角度研究了该问题,但分析深入探讨了改善治疗效果的创新方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3205/11636903/9b56a732221f/gr003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3205/11636903/c72c508a691f/gr001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3205/11636903/5eaf34109a06/gr002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3205/11636903/9b56a732221f/gr003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3205/11636903/c72c508a691f/gr001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3205/11636903/5eaf34109a06/gr002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3205/11636903/9b56a732221f/gr003.jpg

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本文引用的文献

1
Treatment of lung cancer.肺癌的治疗。
Radiol Clin North Am. 2012 Sep;50(5):961-74. doi: 10.1016/j.rcl.2012.06.003.