Retraction: Early bearing fault diagnosis based on improved SFLA and ELM network
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Abstract
In this paper, an extreme learning machine (ELM) network based on an improved shuffled frog leaping algorithm (CCSFLA) is applied in early bearing fault diagnosis. ELM is a new type of single layer...
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- Transactions of the Canadian Society for Mechanical Engineering
- Topic
- Machine Learning and ELM
- Field
- Computer Science
- Canadian institutions
- —
- Funders
- —
- Keywords
- Extreme learning machineBearing (navigation)Fault (geology)Computer scienceArtificial intelligencePattern recognition (psychology)AlgorithmArtificial neural networkGeologySeismology
- Has abstract in OpenAlex
- yes