Abstract: This letter proposes a quantum-enhanced support vector regression (QSVR) approach to cancel the self-interference in full-duplex transceivers. The proposed approach leverages quantum feature ...

The significance of artificial intelligence in contemporary human activities cannot be underestimated. Although the application of this technology in structural engineering is not recent, advancements ...

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ABSTRACT: Support vector regression (SVR) and computational fluid dynamics (CFD) techniques are applied to predict the performance of an automotive torque converter in the design process of turbine ...

Objective: In this study, we aim to identify the predictive variables for hemiplegic shoulder pain (HSP) through machine learning algorithms, select the optimal model and predict the occurrence of HSP ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict a person's income based on their age, weight, current bank account ...

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

To solve the problem of difficult quantitative identification of surface defect depth during laser ultrasonic inspection, a support vector machine-based method for quantitative identification of ...

Abstract: Twin support vector machine (TSVM) is an emerging machine learning model with versatile applicability in classification and regression endeavors. Nevertheless, TSVM confronts noteworthy ...