Abstract: Travel time prediction is essential for the development of advanced traveler information systems. In this paper, we apply support vector regression (SVR) for travel-time predictions and ...

Interpretability of Support Vector Machine (SVM) or Neural Networks (NN) models, examples of black-box models, is a field of study that has recently gained attention, especially for the significant ...

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 ...

Department of Computer Science, School of Engineering & Computer Science, Baylor University, Waco, USA. Department of Electrical & Computer Engineering, Autonomous University of Ciudad Juárez, Ciudad ...

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 ...

Although inherently challenging, the quantification of vehicle emissions has evolved considerably in recent decades and now extends well beyond the original lab-based measurements. Here we’ll explain ...

Support Vector Machines (SVMs) are a powerful and versatile supervised machine learning algorithm primarily used for classification and regression tasks. They excel in high-dimensional spaces and are ...

Machin Learning Full Algorithm (Linear Regression, Decision tree, Random forest, Neural network ,Logistic regression ,Support vector machine ,Naive Bayes ,Clustering ...