The numerical simulation of sheet metal forming processes depends on the accuracy of the
constitutive model used to represent the mechanical behaviour of the materials. The …

We propose a new fault diagnosis model for rolling bearings based on a hybrid kernel
support vector machine (SVM) and Bayesian optimization (BO). The model uses discrete …

The support vector regression (SVR) is a supervised machine learning technique that has
been successfully employed to forecast financial volatility. As the SVR is a kernel-based …

The wear performance of an additively manufactured part is crucial to ensure the
component's functionality and reliability. Nevertheless, wear prediction is arduous due to …

Wide-angle photometric surveys of previously uncharted sky areas or wavelength regimes
will always bring in unexpected sources–novelties or even anomalies–whose existence and …

Falling is one of the main causes of trauma, disability, and death among older people.
Inertial sensors‐based devices are able to detect falls in controlled environments. Often this …

Abstract Support Vector Machines (SVM) are advancing rapidly in the field of machine
learning due to their enhancing performance in categorization and prediction. But it is also …

Artificial intelligence (AI) and machine learning (ML) have influenced every part of our day-to-
day activities in this era of technological advancement, making a living more comfortable on …

In recent years, Kernel based learning algorithm has been receiving increasing attention in
the research domain. Kernel based learning algorithms are related internally with the kernel …

The extensive use of radium during the 20th century for industrial, military and
pharmaceutical purposes has led to a large number of contaminated legacy sites across …