Bearing remaining useful life prediction based on optimized support vector regression model with denoising technique.
Sheng CaoYuchen JiangHao LuoYanming FuXianling LiYunkai WuPublished in: ICPS (2021)
Keyphrases
- regression model
- denoising
- prediction model
- prediction intervals
- support vector
- linear regression model
- support vector regression
- multiple linear regression
- target variable
- regression analysis
- regression methods
- prediction accuracy
- survival analysis
- ls svm
- image denoising
- model selection
- generalized linear models
- kernel regression
- noisy images
- independent variables
- total variation
- multivariate regression
- gaussian process
- interval valued data
- linear model
- generalized linear
- feature selection
- kernel methods
- logistic regression
- explanatory variables
- kernel function
- logistic regression models
- prediction error
- software reliability
- predictive model
- support vector machine
- classification accuracy
- artificial neural networks
- semi parametric
- bp neural network
- loss function
- image restoration
- feature space
- image processing