zhangzw16/SageFormer
Code for IoTJ 2024 paper "SageFormer: Series-Aware Framework for Long-Term Multivariate Time-Series Forecasting".
This helps researchers and data scientists predict future trends from complex sensor data or other interconnected measurements over long periods. It takes in historical multivariate time-series data, such as readings from multiple IoT devices, and outputs accurate long-term forecasts. This is useful for anyone needing to anticipate future behavior in systems with many interacting variables.
No commits in the last 6 months.
Use this if you need to make accurate long-term predictions from data where many different measurements influence each other, such as in smart grids or industrial IoT.
Not ideal if you only need to forecast a single variable, have very short-term prediction needs, or prefer models that don't require handling complex inter-series dependencies.
Stars
86
Forks
8
Language
Python
License
MIT
Category
Last pushed
Mar 29, 2024
Commits (30d)
0
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