Using SHAP and LIME on a public O-RAN dataset, the paper finds airtime, BSR, goodput, and throughput are the most influential parameters for RAN energy consumption.
Prediction and Optimization of Energy Consumption in an Office Building Using Artificial Neural Network and a Genetic Algorithm,
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Integrating Explainable AI for Energy Efficient Open Radio Access Networks
Using SHAP and LIME on a public O-RAN dataset, the paper finds airtime, BSR, goodput, and throughput are the most influential parameters for RAN energy consumption.