A Bayesian least-squares support vector machine method for predicting the remaining useful life of a microwave component
Rapid and accurate lifetime prediction of critical components in a system is important to maintaining the system’s reliable operation. To this end, many lifetime prediction methods have been developed to handle various failure-related data collected in different situations. Among these methods, mach...
Main Authors: | Fuqiang Sun, Xiaoyang Li, Haitao Liao, Xiankun Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
SAGE Publishing
2017-01-01
|
Series: | Advances in Mechanical Engineering |
Online Access: | https://doi.org/10.1177/1687814016685963 |
Similar Items
-
Coupled Least Squares Support Vector Ensemble Machines
by: Dickson Keddy Wornyo, et al.
Published: (2019-06-01) -
Single Directional SMO Algorithm for Least Squares Support Vector Machines
by: Xigao Shao, et al.
Published: (2013-01-01) -
A Bayesian least squares support vector machines based framework for fault diagnosis and failure prognosis
by: Khawaja, Taimoor Saleem
Published: (2010) -
Fault Diagnosis Model of Photovoltaic Array Based on Least Squares Support Vector Machine in Bayesian Framework
by: Jiamin Sun, et al.
Published: (2017-11-01) -
Least squares support vector machine model for coordinate transformation
by: Yao Yevenyo Ziggah, et al.
Published: (2019-04-01)