Pythagorean fuzzy sets and Fermatean fuzzy sets are used to enhance the flexibility of intuitionistic fuzzy sets for decision-making under uncertainty in fuzzy environments. This study presents and compares a new definition of quartic fuzzy sets with intuitionistic, Pythagorean, and Fermatean...

Increasing demand for energy is pushing decision-makers in the Bioethanol Supply Chain Network (BSCN) to adopt second-generation biomass feedstocks to meet sustainability criteria. This study proposes an integrated Machine Learning (ML) and quantitative optimization model to design a Sustainable...

This study introduces the concept of granular F-transform and investigates its basic properties using the theory of fuzzy numbers and horizontal membership functions. We further present a numerical method based on granular F-transform to solve a fuzzy prey–predator model consisting of two prey...

Climate change poses the most significant threat to humanity today. This study examines the global warming trend by analyzing temperature changes over the past century, uncovering alarming results. Various models, including the Random Walk with Drift approach with R programming language, have...

With the extensive applicability of machine learning classification algorithms to a wide spectrum of domains, feature selection (FS) becomes a relevant data preprocessing technique due to the high dimensionality of data used in these domains. While efforts have been made to study various filters...

People have recently begun communicating their thoughts and viewpoints through user-generated multimedia material on social networking websites. This information can be images, text, videos, or audio. With the help of knowledge graphs, it is possible to extract organized knowledge from texts and...

Supplier selection is an important process in supply chain management that sets a foundation for a long-term partnership with suppliers that can greatly contribute to the success or failure of a business. This study aims to identify, validate and propose a comprehensive list of supplier...

Breast cancer is the most common life-threatening cancer in women and one of the leading causes of death. Early diagnosis is one of the best defenses against the spread of breast cancer. Machine learning (ML) tools are now available for cancer detection and prediction. This study presents a...

COVID-19 is a respiratory disease caused by the SARS-CoV-2 contagion, severely disrupted the healthcare infrastructure. Various countries have developed COVID-19 vaccines that have effectively prevented the severe symptoms caused by the virus to a certain extent. However, a small section of...

Early detection of heart complications is highly effective in treating patients with cardiovascular diseases. Various machine learning methods have previously been used for the early detection of heart diseases. However, existing data-driven machine learning (ML) approaches fall short of...