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


Nithya Sri S., Vimala J., KAUSAR N., Ozbilge E., Özbilge E., Pamucar D.

Heliyon, vol.10, no.9, 2024 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 10 Issue: 9
  • Publication Date: 2024
  • Doi Number: 10.1016/j.heliyon.2024.e29863
  • Journal Name: Heliyon
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, CAB Abstracts, Food Science & Technology Abstracts, Veterinary Science Database, Directory of Open Access Journals
  • Keywords: Bipolar Linear Diophantine Fuzzy Hypersoft Set, Bipolar Linear Diophantine Fuzzy Weighted Aggregation Operators, Lung carcinoma, Therapy
  • Yıldız Technical University Affiliated: Yes

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.