KY241

KY241's Stars

• anshulofficial/PyTorch-TransPyTorch-Transformer-for-RUL-Prediction

  Language:Python3

• ZFLiuSystem/MSTSDN-for-RUL-Prediction-of-Aero-engine

  Multi-Scale Temporal-Spatial Feature-based Hybrid Deep Neural Network (MSTSDN) for Predicting RUL of Aero-engine.

  Language:Python61

• huanglinxixi/DTW_RUL_Trajectory

  RUL Prediction based on DTW

  Language:Python11

• AM-2304/rul

  Remaining Useful Life Prediction of Transformers using Bayesian Estimation

  Language:Python4

• Dhruvadityamittal/RUL_Prediction_of_LIB_using_Spatio_temporal_Multimodal_Attention_Networks

  Code for Remaining Useful Life Prediction of Lithium-ion Batteries using Spatio-temporal Multimodal Attention Networks

  Language:Python262

• Frank-Wang-oss/GNN_RUL_Benchmarking

  Benmarking for GNN-based RUL prediction

  Language:Python222

• yushi1006/GGCN-for-RUL-prediction

  Graph Convolutional Network for RUL prediction with multi-sensor signals

  Language:Python191

• XinyuanLiao/AttnPINN-for-RUL-Estimation

  A Framework for Remaining Useful Life Prediction Based on Self-Attention and Physics-Informed Neural Networks

  Language:Python9511

• Junkun-Lu/RUL_Inception-Attention

  Remaining useful life prediction by Transformer-based Model

  Language:Python464

• ZhenghuaNTU/RUL-prediction-using-attention-based-deep-learning-approach

  Language:Python5317

• nicolasoyharcabal/ConvRNN_for_RUL_estimation

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

  Language:Python8112

• mohyunho/NAS_transformer

  Evolutionary Neural Architecture Search on Transformers for RUL Prediction

  Language:Python447

• en-research/ChangePoint-LSTM

  Official code implementation for 'A change point detection integrated remaining useful life estimation model under variable operating conditions (2024)'

  Language:Python61

• hussamaleem/ADDA-with-Transformer-and-Gradient-Monitoring

  Implementation of ADDA with Transformer Architecture and Gradient Monitoring for Remaining Useful Life Estimation through Time Series Data Analysis

  Language:Python6

• mylonasc/gnn-tcnn

  code for paper *Remaining Useful Life Estimation for Engineered Systems Operating under Uncertainty with Causal GraphNets*

  5

• xuweijun-npuer/Nonexchangeable-Split-Conformal-Prediction-of-RUL

  Core codes for the paper ["A General Data-driven Framework for Remaining Useful Life Estimation with Uncertainty Quantification Using Split Conformal Prediction"]

  Language:Python101

• govinda21/Determination_of_Mechanical_tool_RUL

  Determination of Remaining Useful life of Mechanical Tools

  Language:MATLAB31

• ZhiyaoZhang12/UDATrans

  Remaining useful life prediction of aero-engines via domain-invariant and -specific features under the scenarios of working-condition shift

  Language:Python91

• xuqing88/KDnet-RUL

  This code is for paper "KDnet-RUL: A knowledge distillation framework to compress deep neural networks for machine remaining learning useful life prediction

  Language:Python151

• WeiZhengxi/PSECNet_for_RUL

  We have developed an innovative deep learning model, PSECNet, for the prediction of bearing Remaining Useful Life (RUL) on the IEEE 2012 PHM Prognostic Challenge dataset.

  Language:Python26

• Center-of-Excellence-AI-for-Structures/ISTRUST_MODEL

  Code for the paper "Breaking the black box barrier: predicting remaining useful life under uncertainty from raw images with interpretable neural networks". This is a novel interpretable transformer-based model for Remaining Useful Life (RUL) prediction from raw sequential images (frames) representing a composite structure under fatigue loads

  Language:Python13

• SZU-AdvTech-2022/383-Bi-LSTM-Based-Two-Stream-Network-for-Machine-Remaining-Useful-Life-Prediction

  Language:Python6

• mohyunho/NAS_convELM

  Evolutionary optimization of convolutional ELM for remaining useful life prediction

  Language:Python52

• MarcelHenkel/gpm_rul

  generative and predictive models for remaining useful life estimation

  Language:Python5

• ruibing-jin/Bi_LSTM_TS

  This is an official code of "Bi-LSTM based Two-Stream Network for Machine Remaining Useful Life Prediction"

  Language:Python14

• StarMarco/DVAE_torch

  A PyTorch implimentation of a conditional Dynamical Variational Autoencoder for remaining useful life estimation

  Language:Jupyter Notebook102

• rts1988/Remaining_Useful_Life_LSTM

  Remaining Useful Life (RUL) prediction with LSTM and XGBoost (regressio nand classification models)

  Language:Python4

• seanlau-flair/unsupervised-remaining-useful-life-prediction-for-bearings-with-virtual-health-index

  9

• LLerDagu/RUL-FFVE

  Variational encoding based on factorized temporal-channel fusion and feature fusion for interpretable remaining useful life prediction

  Language:Python241

• foryichuanqi/ADVEI-Paper-2024.3-Degradation-path-approximation-for-remaining-useful-life-estimation

  Remaining useful life prediction. Degradation path approximation (DPA) is a highly easy-to-understand and brand-new solution way for data-driven RUL prediction. Many research directions on DPA can be further studied.

  Language:Python13