<ul><li>Forecasting volcanic activity is critical for hazard assessment and risk mitigation.</li><li>Volcanic Radiative Power (VPR) serves as an essential indicator of volcanic activity.</li><li>A study employed Bayesian Regularized Neural Networks (BRNN) to predict future VPR values based on historical data from Fuego Volcano.</li><li>BRNN outperforms other models, achieving the lowest mean squared error and the highest R-squared value.</li></ul>

Forecasting Volcanic Radiative Power (VPR) at Fuego Volcano Using Bayesian Regularized Neural Network

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