Bosh-Kuo / GNN-LSTM-based-Fusion-Model-for-Structural-Dynamic-Responses-PredictionLinks
A novel GNN-LSTM-based fusion model which could accurately predict the seismic responses of multiple structures with different geometry.
☆83Updated last year
Alternatives and similar repositories for GNN-LSTM-based-Fusion-Model-for-Structural-Dynamic-Responses-Prediction
Users that are interested in GNN-LSTM-based-Fusion-Model-for-Structural-Dynamic-Responses-Prediction are comparing it to the libraries listed below
Sorting:
- ☆11Updated last year
- Deep Learning for Structural Health monitoring☆19Updated last year
- Multivariate Time Series Forecasting with Graph Neural Networks☆13Updated 3 years ago
- Recursive long short-term memory network for predicting nonlinear structural seismic response☆19Updated 3 years ago
- a multivariate time series deep spatiotemporal forecasting model with graph neural network (MDST-GNN) is proposed to solve the existing …☆32Updated 3 years ago
- Industrial process, Silicon content, molten iron quality (MIQ) prediction, soft sensor, deep learning, sintering process, blast furnace i…☆29Updated last year
- A sequential combination of LSTM and MLP for the prediction of cutterhead torque for TBM.☆13Updated 4 years ago
- MVTS Classification with GCN-LSTM☆25Updated 3 years ago
- Physics-guided Convolutional Neural Network☆68Updated 5 years ago
- Code for the paper "Multivariate Time Series Prediction of Complex Systems Based on Graph Neural Networks with Location Embedding Graph S…☆24Updated 2 years ago
- Air pollution prediction based on improved Informer model: a case study applied to the Yan'an city of China☆15Updated 2 years ago
- Pytorch implementation of various traffic prediction modules(FC-LSTM, GRU, GCN, Diffusion Conv, Temporal Attention, etc.)☆10Updated last year
- Physics Informed Neural Network for Time Series Forecasting☆13Updated 2 years ago
- Theory-guided deep-learning load forecasting is a short-term load forecasting model that combines domain knowledge and machine learning a…☆31Updated 3 years ago
- Time series forecasting especially in LSTF compare，include Informer, Autoformer, Reformer, Pyraformer, FEDformer, Transformer, MTGNN, LST…☆123Updated 3 years ago
- Short-term Air Quality Prediction Based on EMD-Transformer-BiLSTM☆42Updated last year
- Python scripts for wind turbine main bearing fatigue life estimation with physics-informed neural networks☆114Updated 3 years ago
- This repository presents a series of analysis on the performance of Physics-Informed Neural Networks in vibrational systems. The limitati…☆12Updated 2 years ago
- Deep LSTM for highly nonlinear system modeling☆56Updated 6 years ago
- We introduce an innovative physics-informed LSTM framework for metamodeling of nonlinear structural systems with scarce data.☆96Updated 2 years ago
- Physics-guided Neural Networks (PGNN) : An Application In Lake Temperature Modelling☆112Updated 4 years ago
- This is a PyTorch implementation of STGAGRTN in the Spatial-Temporal Graph Attention Gated Recurrent Transformer Network for Traffic Flow…☆20Updated last year
- Codes of our journal paper: Indirect identification of bridge frequencies using a four-wheel vehicle: Theory and three-dimensional simula…☆19Updated last month
- Code for Deep Spatio Temporal Wind Power Forecasting☆51Updated 3 years ago
- A Framework for Remaining Useful Life Prediction Based on Self-Attention and Physics-Informed Neural Networks☆116Updated last year
- Multi-Step Spatio-Temporal Forecasting: https://authors.elsevier.com/sd/article/S0306-2619(22)01822-0☆82Updated last year
- Tree seed algorithm and Particle Swarm algorithm are used for searching the LSTM hyper parameters☆11Updated 2 years ago
- An Ensemble DL Model Tuned with Genetic Algorithm for Oil Production Forecasting.☆72Updated 2 years ago
- ☆121Updated last year
- ResNet_LSTM_GCN☆13Updated 2 years ago