The future performance of stock markets is the most crucial factor in portfolio creation. As
machine learning technique is advancing, new possibilities have opened up for …

Alzheimer's disease (AD) is the most pervasive form of dementia, resulting in severe
psychosocial effects such as affecting personality, reasoning, emotions, and memory …

Twin support vector machines (TSVMs) have been successfully employed for binary
classification problems. With the advent of machine learning algorithms, data have …

Data classification is a key domain of research in real-world applications. One of the big
challenges of real-world data classification is to tackle the presence of noise and outliers. In …

Low-rank matrix learning techniques, especially support matrix machine (SMM) approach,
have significantly altered mechanical fault diagnosis by efficiently uncovering correlations …

Twin support vector machine is one of the most prominent techniques for classification
problems. It has been applied in various real world applications due to its less computational …

At present, the parameters of the multiple birth support vector machine (MBSVM) are mainly
determined by experience or artificially specified by the grid method. Both of these methods …

The intuitionistic fuzzy twin support vector machine for multi-categorization is developed in
this study, which incorporates both structural and empirical risk concepts. In this method …

In classification problems, the data samples belonging to different classes have different
number of samples. Sometimes, the imbalance in the number of samples of each class is …

Wheelset bearing is the most critical component in High-Speed Train (HST) and crucial for
HST safe and efficient operation. As a wide applying method for bearing health monitoring …