MingweiJia / GCN-based_soft_sensorLinks
paper: Development of GCN-based soft sensor for quality prediction of process industry
☆10Updated 11 months ago
Alternatives and similar repositories for GCN-based_soft_sensor
Users that are interested in GCN-based_soft_sensor are comparing it to the libraries listed below
Sorting:
- Soft sensor modelling using multiple machine learning algorithms☆23Updated 5 years ago
- Code Implement of A Data-driven Self-supervised LSTM-DeepFM Model for Industrial Soft Sensor☆28Updated 3 years ago
- 本科毕业设计 - 基于数据解析的化工生产过程诊断☆12Updated 3 years ago
- Industrial process, Silicon content, molten iron quality (MIQ) prediction, soft sensor, deep learning, sintering process, blast furnace i…☆26Updated 11 months ago
- ☆89Updated 3 years ago
- Adaptive Soft Sensors☆17Updated 5 years ago
- An semi-supervised extension based on VAE for Regression, demonstrate its performance on two soft sensor benchmark problems.☆22Updated last year
- ☆27Updated 2 years ago
- Soft Sensor with Variational Inference Technique☆19Updated 7 months ago
- Code for the paper "Multivariate Time Series Prediction of Complex Systems Based on Graph Neural Networks with Location Embedding Graph S…☆25Updated 2 years ago
- Fault Diagnosis of Tennessee Eastman Chemical process using Neural Networks☆40Updated 6 years ago
- Github repo for the research paper titled "Integrating Adaptive Moving Window and Just-in-Time Learning Paradigms for Soft-Sensor Design"☆20Updated 5 years ago
- Multivariate Time Series Forecasting with Graph Neural Networks☆13Updated 3 years ago
- Data driven fault detection in chemical processes: Application to Tennessee Eastman Plant☆31Updated 4 years ago
- Code for thesis "Graph Dynamic Autoencoder for Fault Detection"☆18Updated 3 years ago
- A Digital Twin prototype for aircraft engine health management in order to identify possible faults and to predict its remaining useful l…☆10Updated 3 months ago
- a simple example of fault diagnose with TE(tennessee-eastman) dataset, using PCA☆13Updated 3 years ago
- A novel GNN-LSTM-based fusion model which could accurately predict the seismic responses of multiple structures with different geometry.☆69Updated last year
- Unified index for unsupervised fault detection in a Tennessee Eastman Process☆13Updated 5 years ago
- A hybrid approach using physical information (PI) lightweight temporal convolutional neural networks (PI-TCN) for remaining useful life (…☆29Updated 2 years ago
- ☆12Updated 2 years ago
- Official codes for "Addressing Information Asymmetry: Deep Temporal Causality Discovery for Mixed Time Series" (TPAMI 2025)☆11Updated 2 months ago
- Early access articles, Journals, and Conferences☆26Updated 4 years ago
- Pytorch Implementation of LSTM-SAE(Long Short Term Memory - Stacked AutoEncoder)☆24Updated 8 months ago
- BG-CNN: A Hybrid Fault Diagnosis Method for Improved Fault Isolation. This repository presents the BG-CNN method, a novel approach that …☆10Updated 11 months ago
- This project aims to propose a TCN-Based Bayesian neural nework that is used for remaining useful life prediction.☆22Updated 3 years ago
- Multi-mode Fault Diagnosis Datasets with TE process (MMFDD-TEP) can be used for the purpose of comparison studies or validation of algor…☆27Updated last year
- Chemical Process Fault Detection Using Long Short-Term Memory Recurrent Neural Network.☆33Updated 9 months ago
- Implementation of the Slow Feature Analysis algorithm for unsupervised learning☆11Updated 2 years ago
- Short-term Air Quality Prediction Based on EMD-Transformer-BiLSTM☆35Updated last year