equinor/TimeSeriesAnalysis
Library for dynamic time-series modeling, identification and simulation. Focus on dealing with non-ideal real world datasets, and applications to industrial processes and -pid-feedback loops. Robust and fast for advanced analytics. Built on .NET to run anywhere.
This tool helps operations engineers and process control specialists build dynamic models and simulators directly from their industrial time-series data. You feed it historical data from physical systems like sensors and controllers, and it produces explainable models that can simulate how your process will respond to changes or identify anomalies. This is ideal for those managing complex industrial processes.
Use this if you need to create 'digital twin' models of industrial processes, predict system behavior, or detect performance issues at scale from your existing time-series data.
Not ideal if you prefer to build models from first physical principles or require highly complex, black-box machine learning models with many free parameters.
Stars
20
Forks
3
Language
C#
License
Apache-2.0
Category
Last pushed
Feb 10, 2026
Commits (30d)
0
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