Urban transport system development often involves a central decision-making process by
local government representatives or transport company managers. It is imperative to align …

Entropy plays a vital role within fuzzy set theory as it quantifies the level of uncertainty
present in the data. This study proposes a novel entropy measure tailored for Picture Fuzzy …

The ambiguous sets have recently been proposed to represent inherent uncertainties,
imprecision, and vague information. In this study, we generalize the concept of the …

Digital devices are an integral component of the healthcare sector. With the advancement of
modern technology with Artificial Intelligence (AI) and Machine Learning (ML), an automated …

To tackle issues associated with phishing website attacks, the study conducted rigorous
experiments on RF, GB, and CATB classifiers. Since each classifier was an ensemble …

This paper presents a comprehensive exploration of machine learning algorithms (MLAs)
and feature selection techniques for accurate heart disease prediction (HDP) in modern …

This study addresses the challenge of differentiating between bipolar disorder II (BD II) and
borderline personality disorder (BPD), which is complicated by overlapping symptoms. To …

Feature selection identifies the relevant features and removes the irrelevant and redundant
ones, intending to obtain the best-performing feature subset. This paper proposes a new …

Purpose Cancer stands as a formidable adversary on the global stage, claiming a significant
number of lives each year. Yet, amidst this sobering reality, the importance of early detection …

This study aims to develop a recommendation engine methodology to enhance the model's
effectiveness and efficiency. The proposed model is commonly used to assign or propose a …