Optimizing SVM’s parameters based on backtracking search optimization algorithm for gear fault diagnosis

Optimizing SVM’s parameters based on backtracking search optimization algorithm for gear fault diagnosis

The accuracy of a support vector machine (SVM) classifier is decided by the selection of optimal parameters for the SVM. The Backtracking Search Optimization Algorithm (BSA) is often applied to resolve the global optimization problem and adapted to optimize SVM parameters. In this research, a SVM pa...

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Bibliographic Details
Main Authors: Vantrong Thai, Junsheng Cheng, Viethung Nguyen, Phuonganh Daothi
Format: Article
Language:English
Published: JVE International 2019-02-01
Series:Journal of Vibroengineering
Subjects:
signal processing
fault detection
gears
artificial neural networks
backtracking search optimization algorithm
Online Access:https://www.jvejournals.com/article/19859

Internet

https://www.jvejournals.com/article/19859

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