This paper reports the experimental results on the application of different pattern recognition algorithms to the evaluation of earthquake risk for real geological structures. The study area used for the experiments is related to a well-known geological structure representing a "triangular valley over bedrock". Performances obtained by two neural networks and two statistical classifiers are reported and compared. The advantages provided by the use of methods for combining multiple classifiers are also discussed and the related results reported. (C) 1997 Elsevier Science B.V.

Application of neural networks and statistical pattern recognition algorithms to earthquake risk evaluation

ROLI, FABIO
1997-01-01

Abstract

This paper reports the experimental results on the application of different pattern recognition algorithms to the evaluation of earthquake risk for real geological structures. The study area used for the experiments is related to a well-known geological structure representing a "triangular valley over bedrock". Performances obtained by two neural networks and two statistical classifiers are reported and compared. The advantages provided by the use of methods for combining multiple classifiers are also discussed and the related results reported. (C) 1997 Elsevier Science B.V.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1086734
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