Using Artificial Intelligence to forecast the location of earthquake and post-earthquake-induced landslides
This presentation will be on the progress we've made trying to forecast landslides caused by earthquakes and precipitation. Good quality input datasets are used to train a Tensorflow / Keras Sequential neural network whose parameters are determined by using Bayesian hyperparameter optimization (BayesianOptimization), and whose training details are established by using KFold (sklearn) iterations with the EarlyStopping monitor. The resulting trained neural network is then applied to all the available data, and some graphs are created to show the results.
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