Machine Learning models for seismic signals parameters
Sonia Thomas
Broschiertes Buch

Machine Learning models for seismic signals parameters

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In this work, advanced machine learning algorithms are used to develop predictive models for forecasting ground motion parameters. The machine learning algorithms used are extreme learning machines (ELM), support vector regression (SVR) and its three variations, decision trees and hybrid algorithm ANFIS (adaptive neuro fuzzy inference system). A novel neuro fuzzy algorithm, RANFIS (randomized ANFIS) is also proposed for forecasting ground motion parameters. This advanced learning machine integrates the explicit knowledge of the fuzzy systems with the learning capabilities of neural networks, a...