# Data-driven prediction of the: L–H transition power threshold in the EAST tokamak using ensemble learning regression

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/data-driven-prediction-of-the-l-h-transition-power-threshold-in-the-east-tokamak/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Wanli Lyu,Hui Wang,Ping Wang,Xin Lin,dengdi sun,Xiao Wang,Zheng Deng,Linming Shao,Qingquan Yang,Jin Tang,Guo Sheng Xu |
| Citations | 0 |
| DOI | 10.1088/1361-6587/ae533c |
| Fields | Engineering,Materials Science,Physics and Astronomy |
| Open Access | true |
| OA Status | bronze |
| OA URL | https://iopscience.iop.org/article/10.1088/1361-6587/ae533c/pdf |
| OpenAlex ID | https://openalex.org/W7138059261 |
| Type | article |
| Year | 2026 |

## Paper authors

- [Hui Wang](https://scholariq.org/researchers/hui-wang-5/)

## Paper primary topic

- [Magnetic confinement fusion research](https://scholariq.org/topics/magnetic-confinement-fusion-research/)

## Paper topics

- [Magnetic confinement fusion research](https://scholariq.org/topics/magnetic-confinement-fusion-research/)
- [Fusion materials and technologies](https://scholariq.org/topics/fusion-materials-and-technologies/)
- [Nuclear reactor physics and engineering](https://scholariq.org/topics/nuclear-reactor-physics-and-engineering/)

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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.