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Seismic Design Value Evaluation Based on Checking Records and Site Geological Conditions Using Artificial Neural Networks
2013
Abstract and Applied Analysis
This study proposes an improved computational neural network model that uses three seismic parameters (i.e., local magnitude, epicentral distance, and epicenter depth) and two geological conditions (i.e., shear wave velocity and standard penetration test value) as the inputs for predicting peak ground acceleration—the key element for evaluating earthquake response. Initial comparison results show that a neural network model with three neurons in the hidden layer can achieve relatively better
doi:10.1155/2013/242941
fatcat:py4fg57hjbfq5aictmlh25cvsi