wentao-zang Goto Github PK
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wentao-zang's Projects
attnpinn-for-rul-estimation
A Framework for Remaining Useful Life Prediction Based on Self-Attention and Physics-Informed Neural Networks
chinese-text-classification-pytorch
中文文本分类，TextCNN，TextRNN，FastText，TextRCNN，BiLSTM_Attention，DPCNN，Transformer，基于pytorch，开箱即用。
cloudcompare
CloudCompare main repository
cnn-bilstm-attention-time-series-prediction_keras
CNN+BiLSTM+Attention Multivariate Time Series Prediction implemented by Keras
deep-residual-networks
Deep Residual Learning for Image Recognition
estimation-of-remaining-useful-life-using-cnn
Convolutional Neural Network based regression approach for estimating machinery's remaining useful life
gulimall
谷粒商城
iapmhad
活动翼面数据采集与分析后端
iapmhadweb
活动翼面制孔机器人前端
leetcode
LeetCode Problems' Solutions
leetcode-master
《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀
lstm
Maybe the 1st tool wear forecasting by DL
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.
pytorch-lstm-for-rul-prediction
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.
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.
rul-net
Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine
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