# New imbalanced bearing fault diagnosis method based on Sample-characteristic Oversampling TechniquE (SCOTE) and multi-class LS-SVM

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/new-imbalanced-bearing-fault-diagnosis-method-based-on-sample-characteristic/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Jianan Wei,Haisong Huang,Liguo Yao,Yao Hu,Qingsong Fan,Dong Huang |
| Citations | 153 |
| DOI | 10.1016/j.asoc.2020.107043 |
| Fields | Computer Science,Engineering |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3112362363 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Dong Huang](https://scholariq.org/researchers/dong-huang/)

## Paper primary topic

- [Imbalanced Data Classification Techniques](https://scholariq.org/topics/imbalanced-data-classification-techniques/)

## Paper topics

- [Imbalanced Data Classification Techniques](https://scholariq.org/topics/imbalanced-data-classification-techniques/)
- [Machine Fault Diagnosis Techniques](https://scholariq.org/topics/machine-fault-diagnosis-techniques/)
- [Industrial Vision Systems and Defect Detection](https://scholariq.org/topics/industrial-vision-systems-and-defect-detection/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.