A novel hybrid extreme learning machine-whale optimization algorithm for bearing fault diagnosis
In order to avoid fatalities and ensure safe operation, a good and accurate diagnosis method is required. A diagnosis method based on extreme learning machine (ELM) has attracted much attention and the ELM method had been applied in various field of study. The advantages of the ELM method which are...
Saved in:
Main Authors: | Firdaus Isham, M., Saufi, M. S. R., A. R., Amirul |
---|---|
Format: | Conference or Workshop Item |
Published: |
2022
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/99371/ http://dx.doi.org/10.1007/978-981-16-8690-0_55 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A novel hybrid extreme learning machine-whale optimization algorithm for bearing fault diagnosis
by: Isham, M. Firdaus, et al.
Published: (2022) -
Bearing fault diagnosis using extreme learning machine based on artificial gorilla troops optimizer
by: Isham, Muhd. Firdaus, et al.
Published: (2023) -
CLASSIFICATION OF BEARING FAULTS USING EXTREME
LEARNING MACHINE ALGORITHMS
by: TEH, CHOON KEONG
Published: (2017) -
A Novel Hybrid Model for Forecasting China Carbon Price Using CEEMDAN and Extreme Learning Machine Optimized by Whale Algorithm
by: Li, Ni, et al.
Published: (2023) -
Bearing fault diagnosis using deep sparse autoencoder
by: Saufi, S. R., et al.
Published: (2021)