A time series data analysis algorithm library for industrial scenarios
Project description
This is an algorithm library dedicated to industrial time series data analysis, including 5 types of algorithms, 20 algorithms, experimentally verified on actual industrial production data and public datasets, and 25 algorithm instances are formed, as follows
| Type | Algorithm |
|---|---|
| Describe | MICAD,MOCAR,RBS,TSCA |
| Decide | Il_Std,Qcd,SDE_DK |
| Dianosse | MCFMAAE,MGAHGM |
| Forecast | MSNET,PID4LaTe,STD_Phy,STDNet,TDG4MSF,CGRAN,MMPNN,MCRN,TALS,MANO |
| Control | PMCCL |
Quick Install
We recommend to first setup a clean Python environment for your project with Python 3.8+ using conda. Once your environment is set up you can install darts using pip:
pip install Industrial_time_series_analysis
Dependencies
Python(>=3.8) Torch(>=1.12.0) Numpy(>=1.19.5) threadpoolctl(>=3.1.0) Scipy(>=1.6.0)
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