Septemc/CGTST-CausalGate
以化学工业反应为例的因果门控时间序列神经网络 / Causal gated time series neural network based on chemical industry reaction
This project helps chemical engineers understand which factors most significantly influence their industrial chemical reactions over time. It takes in time-series data from various sensors and process parameters, then outputs a clear assessment of how each input variable causally impacts the reaction. Chemical process engineers and control system designers can use this to optimize reactions and troubleshoot issues.
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Use this if you need to determine the causal relationships between different variables in a complex industrial chemical reaction to improve process understanding and control.
Not ideal if your data is not time-series based or if you are not working with chemical industrial processes.
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Python
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Last pushed
Oct 08, 2024
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