noemalRoy

noemalRoy's Stars

• TBdevellopper/PRONOSTIA

  PRONOSTIA-FEMTO dataset: Preparation & application examples

  7

• ddrrrr/projectRUL2

  Language:Python6418

• Abhijit-Bhumireddy99/RUL_Prediction

  remaining Useful Life (RUL) Prediction of Mechanical Bearings using Continuous Wavelet Transform (CWT), Convolution Neural Network (CNN), and Long Short Term Memory (LSTM) unit

  Language:Jupyter Notebook13817

• tilman151/rul-datasets

  A collection of datasets for RUL estimation as Lightning Data Modules.

  Language:Python412

• tilman151/rul-adapt

  A collection of unsupervised domain adaption algorithms for RUL estimation.

  Language:Python343

• hustcxl/Deep-learning-in-PHM

  Deep learning in PHM，Deep learning in fault diagnosis，Deep learning in remaining useful life prediction

  420103

• nicolasoyharcabal/ConvRNN_for_RUL_estimation

  Code used in Thesis "Convolutional Recurrent Neural Networks for Remaining Useful Life Prediction in Mechanical Systems".

  Language:Python8112

• lankuohsing/Remaining-Useful-Life-Prediction-RNN

  Remaining Useful Life Prediction Using RNN/LSTM/GRU Neural Networks

  Language:Python12720

• jiaxiang-cheng/PyTorch-Transformer-for-RUL-Prediction

  Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo, Y., Wu, Q., Li, X., & Huang, B. (2021). Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit. Journal of Intelligent Manufacturing, 1-10.

  Language:Python24248

• DA-southampton/NLP_ability

  总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力

  Language:Python7k1.2k

• BBT0524/diagnose_fault_by_vibration

  毕设研究课题：根据轴承的振动序列数据来诊断轴承故障。

  Language:Python12024

• CDTrans/CDTrans

  [ICLR2022] CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation

  Language:Python32039

• Junkun-Lu/RUL_Inception-Attention

  Remaining useful life prediction by Transformer-based Model

  Language:Python444

• opensuh/GMFE

  Generalized Multiscale Feature Extraction for Remaining Useful Life Prediction of Bearings with Generative Adversarial Networks

  Language:Python418

• tianyushou/bearingRUL

  Using LSTM to predict bearings' remaining useful life

  Language:Python463

• inovex/RCIS2021-degradation-estimation-bearing-vessels

  Language:Python83

• ddrrrr/projectRUL

  to prediction the remain useful life of bearing based on 2012 PHM data

  Language:Python27363

• viralpandey/rul_using_CNN_LSTM

  Predict remaining useful life of a machine from it's historical data using CNN and LSTM

  Language:Jupyter Notebook2916

• ShubhankarKG/RUL_Prediction_SVM

  Bearing remaining useful life prediction using support vector machine and hybrid degradation tracking model - Implementation of Research Paper : https://doi.org/10.1016/j.isatra.2019.08.058

  Language:Jupyter Notebook434

• jindongwang/transferlearning

  Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

  Language:Python13.6k3.8k

• jiaxiang-cheng/PyTorch-CNN-for-RUL-Prediction

  PyTorch implementation of CNN for remaining useful life prediction. Inspired by Babu, G. S., Zhao, P., & Li, X. L. (2016, April). Deep convolutional neural network-based regression approach for estimation of remaining useful life. In International conference on database systems for advanced applications (pp. 214-228). Springer, Cham.

  Language:Python8719