20250805 meeting
Contents
Introduction
The following uses the TSMixerModel of the dart module to fill in the next 10 days.
Experiment
gallery_made_with_nanogallery_exp2
| Method | Value |
|---|---|
| MSPE | 4.502955 |
| RMSPE | 5.508323 |
| MAPE | 4.502955 |
| MSPE% | 0.015959 |
| RMSPE% | 0.328823 |
| MAPE% | 0.015959 |
Conclusion
The result of this experiment are all integers, we need to fix it!
Execution result reference
| |
Epilogue
Environment
- Local Operating System: Windows 11 24H2
- Programming Language: Python 3.12.9
- Computing Platform: National Center for High-Performance Computing (NCHC) – Taiwan AI Cloud
- Operating System: Ubuntu
- Miniconda
- GPU: NVIDIA Tesla V100 32GB GPU
- CUDA 12.8 driver
- Programming Language: Python 3.10.16 for Linux
Further Learning
- I tested this project on the GitHub repository.
References
Juan Lopez Alcaraz, Nils Strodthoff. (2022). Diffusion-based time series imputation and forecasting with structured state space models. Transactions on Machine Learning Research. Retrieved from https://openreview.net/forum?id=hHiIbk7ApW
SSSD. (2022). GitHub. Retrieved from https://github.com/AI4HealthUOL/SSSD
SSSD_CP. (2024). GitHub. Retrieved from https://github.com/egpivo/SSSD_CP
近兩年小時值查詢. (n.d.). 環境部 - 空氣品質監測網. Retrieved from https://airtw.moenv.gov.tw/CHT/Query/InsValue.aspx



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