Abstract: Federated learning (FL) has emerged as a powerful paradigm for decentralized machine learning, enabling collaborative model training across diverse clients without sharing raw data. However, ...

Abstract: Support Vector Machine (SVM) is a supervised machine learning algorithm, which is used for robust and accurate classification. Despite its advantages, its classification speed deteriorates ...

Aviation engines, as vital aircraft components, encounter challenges in Condition Monitoring (CM) signal fault diagnosis, including low accuracy and poor real-time performance. To tackle these, by ...

Although an intracranial aneurysm (IA) is widespread and fatal, few drugs can be used to prevent its rupture. This study explored the molecular mechanism and potential targets of IA rupture through ...

This study aimed to classifying wheat genotypes using support vector machines (SVMs) improved with ensemble algorithms and optimization techniques. Utilizing data from 302 wheat genotypes and 14 ...

There are many methods for processing spectral data, such as least squares, artificial neural networks, etc. The core idea of the SVM algorithm is to map data into a high-dimensional space, making it ...

Support Vector Machines (SVM) are widely used in machine learning for classification and regression tasks. However, the performance of an SVM model depends heavily on its parameter settings, such as ...

In this paper, a feature selection method combining the reliefF and SVM-RFE algorithm is proposed. This algorithm integrates the weight vector from the reliefF into SVM-RFE method. In this method, the ...