# jiaxiang-cheng/PyTorch-LSTM-for-RUL-Prediction

<https://repo.masters-masters.com/en/repos/jiaxiang-cheng/PyTorch-LSTM-for-RUL-Prediction>

[Home](https://repo.masters-masters.com/en) › [jiaxiang-cheng](https://repo.masters-masters.com/en/owners/jiaxiang-cheng) › [PyTorch-LSTM-for-RUL-Prediction](https://repo.masters-masters.com/en/repos/jiaxiang-cheng/PyTorch-LSTM-for-RUL-Prediction)

jiaxiang-cheng/PyTorch-LSTM-for-RUL-Prediction has 187 stars on GitHub. Its RepoMasters card: Prototype tier. PyTorch implementation of remaining useful life…

| Field | Value |
| --- | --- |
| Owner | [jiaxiang-cheng](https://repo.masters-masters.com/en/owners/jiaxiang-cheng) |
| Stars | 187 |
| Forks | 26 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | Apache-2.0 |
| Created | 2021 |
| Topics | lstm, lstm-neural-networks, remaining-useful-life, pytorch, cmapss |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [jiaxiang-cheng/PyTorch-LSTM-for-RUL-Prediction](https://github.com/jiaxiang-cheng/PyTorch-LSTM-for-RUL-Prediction) |

## Repository

PyTorch implementation of remaining useful life prediction with long-short term memories (LSTM), performing on NASA C-MAPSS data sets. Partially inspired by Zheng, S., Ristovski, K., Farahat, A., & Gupta, C. (2017, June). Long short-term memory network for remaining useful life estimation.

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

## More repos by jiaxiang-cheng

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- [jiaxiang-cheng/PyTorch-CNN-for-RUL-Prediction · ★ 105 · Python · Prototype](https://repo.masters-masters.com/en/repos/jiaxiang-cheng/PyTorch-CNN-for-RUL-Prediction)

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