harry321abc / Seq2Seq-Prediction

This is the code implementation for our 2021+ PSE conference paper "Continuous Manufacturing Process Sequential Prediction using Temporal Convolutional Network".

Seq2Seq-Prediction

This is the code implementation for our 2021+ PSE conference paper "Continuous Manufacturing Process Sequential Prediction using Temporal Convolutional Network".

Model

We have implemented recurrent neural networks (rnn.py,lstm.py), temporal convolutional netwrok(TCN.py),and modified transformer/informer models(transformer.py,informerT1.py,informerT2.py) for the seq2seq predictions in continuous manufacturing process.

Dataset

We provided a dataset from a sintering process. If you want to retrain the model with your own data, you can use the class Dataset_custom