What problems does this solve? There are many models of climate change; what marginal benefit does this one provide? Also, is it being used?
The abstract seems to focus on the technique, Model Predictive Control technique, but what dis/advantages does it have? Or maybe the novel part is the neural network.
"... a novel system utilizing the Model Predictive Control technique (MPC) to optimize greenhouse gas emissions reductions. Through a receding horizon approach, the system dynamically adjusts carbon dioxide, methane, and other greenhouse gases emissions to maintain temperature anomalies within safe limits. The system operates in two phases: first, applying MPC to minimize temperature anomalies by optimizing emissions from 2025 to 2100; second, embedding an artificial neural network trained to capture the relationship between policy decisions and greenhouse gas emissions into an optimization process that identifies the policy set required to achieve a desired emissions pathway."
dlcarrier 2 days ago [-]
Why is this published in IEEE? Is nature going to start publishing articles about Space–Time Modulation of a Multimode Electrically Small Antenna for Increased Matching and Efficiency Bandwidths?
CGMthrowaway 2 days ago [-]
At first blush this seems quite a bit less ham-handed than "net zero by 2030" type of goals, so that could be a good thing.
czbond 2 days ago [-]
Very excited to dive into this, thanks for sharing. Looking to apply it at the private sector
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The abstract seems to focus on the technique, Model Predictive Control technique, but what dis/advantages does it have? Or maybe the novel part is the neural network.
"... a novel system utilizing the Model Predictive Control technique (MPC) to optimize greenhouse gas emissions reductions. Through a receding horizon approach, the system dynamically adjusts carbon dioxide, methane, and other greenhouse gases emissions to maintain temperature anomalies within safe limits. The system operates in two phases: first, applying MPC to minimize temperature anomalies by optimizing emissions from 2025 to 2100; second, embedding an artificial neural network trained to capture the relationship between policy decisions and greenhouse gas emissions into an optimization process that identifies the policy set required to achieve a desired emissions pathway."