Traffic_flow_code
short term traffic forecasting using deep learning architectures
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Tsai | 4,659 |  | 2 | a month ago | 47 | November 13, 2023 | 71 | apache-2.0 | Jupyter Notebook | |
| Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai | ||||||||||
| Web Traffic Forecasting | 552 | 6 years ago | 12 | Python | ||||||
| Kaggle | Web Traffic Forecasting 📈 | ||||||||||
| Traffic_prediction | 237 | 6 months ago | mit | TeX | ||||||
| Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries). | ||||||||||
| Seriesnet | 202 | 2 years ago | mit | Python | ||||||
| Time series prediction using dilated causal convolutional neural nets (temporal CNN) | ||||||||||
| Kaggle Competition Favorita | 138 | 6 years ago | 5 | mit | Python | |||||
| 5th place solution for Kaggle competition Favorita Grocery Sales Forecasting | ||||||||||
| Tcdf | 121 | 5 years ago | gpl-3.0 | Jupyter Notebook | ||||||
| Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series | ||||||||||
| Gan Rnn_timeseries Imputation | 118 | 2 years ago | 6 | mit | Jupyter Notebook | |||||
| Recurrent GAN for imputation of time series data. Implemented in TensorFlow 2 on Wikipedia Web Traffic Forecast dataset from Kaggle. | ||||||||||
| Kaggle Web Traffic Time Series Forecasting | 24 | 5 years ago | Jupyter Notebook | |||||||
| Solution to Kaggle - Web Traffic Time Series Forecasting | ||||||||||
| Solar Rad Forecasting | 24 | 2 years ago | n,ull | Jupyter Notebook | ||||||
| In these notebooks the entire research and implementation process carried out for the construction of various machine learning models based on neural networks that are capable of predicting levels of solar radiation is captured given a set of historical data taken by meteorological stations. | ||||||||||
| Encoderdecoder | 15 | 4 months ago | Python | |||||||
| Hybrid CNN-LSTM Encoder Decoder algorithm for multi-step reservoir storage volume forecasting | ||||||||||
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