Abstract: Existing machine learning-based methods for series arc fault (SAF) identification still suffer from slow training speed when dealing with large-scale SAF datasets. For this reason, we ...

Abstract: In this study, the application of support vector machine (SVM) in modern industrial fault diagnosis is mainly analyzed. As an advanced machine learning algorithm, SVM can effectively ...

Our study focused on using the Big Five personality inventory to predict traits from students' smartphone sensor data collected over 2 months under the Horizon Europe project. Through correlation ...

Even though traditional databases now support vector types, vector-native databases have the edge for AI development. Here’s how to choose. AI is turning the idea of a database on its head.

Background: Alterations in brain structure have been suggested to be associated with bulimia nervosa (BN). This study aimed to employ machine learning (ML) methods based on diffusion tensor imaging ...

ABSTRACT: In the field of machine learning, support vector machine (SVM) is popular for its powerful performance in classification tasks. However, this method could be adversely affected by data ...

In the era of big data and artificial intelligence, machine learning is one of the hot issues in the field of credit rating. On the basis of combing the literature on credit rating methods at home and ...

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 ...

(CGCSTCD'2017) An easy, flexible, and accurate plate recognition project for Chinese licenses in unconstrained situations. CGCSTCD = China Graduate Contest on Smart-city Technology and Creative Design ...