Using Machine Learning to Anticipate Rare Catastrophic Occurrences: Earthquakes and Pandemics
Scientists have developed a new method for predicting rare catastrophic events, such as earthquakes, pandemics, or rogue waves, using a combination of advanced machine learning and sequential sampling techniques, according to researchers from Brown University and MIT. Traditional predictive models often fail when it comes to forecasting these types of extreme events, as they are statistically so rare that there is not enough data to make accurate predictions. However, the new approach developed by the researchers uses a combination of machine learning and sequential sampling to identify patterns and make predictions about rare events, even with limited data. In the study, the researchers applied this method to identifying parameters and ranges of probabilities for dangerous spikes during a pandemic, predicting rogue waves, and estimating when a ship will crack in half due to stress. For example, they were able to discover and quantify when rogue waves will form by an...
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