Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Improvement of HVSR technique by self-organizing map (SOM) analysis
AbstractData interpretation is one of the most important and thorny tasks in geosciences. Difficulties occur especially in non-invasive geophysical techniques and/or when the data that have to be analyzed are multidimensional, non-linear and highly noisy. Another important task is to ensure an efficient automatic data analysis, in order to allow a data interpretation as independent as possible from any a priori knowledge. This paper describes the post-processing application of a kind of neural network (self-organizing map, SOM) to the identification of the fundamental HVSR frequency of a given site. SOM results can be represented as two-dimensional maps, with a non-parametric mapping that projects the high dimensional original dataset in a fashion that provides both an unsupervised clustering and a highly visual representation of the data relationships. This innovative application of the SOM algorithm is presented with a case study related to the characterization of a mineral deposit.
Improvement of HVSR technique by self-organizing map (SOM) analysis
AbstractData interpretation is one of the most important and thorny tasks in geosciences. Difficulties occur especially in non-invasive geophysical techniques and/or when the data that have to be analyzed are multidimensional, non-linear and highly noisy. Another important task is to ensure an efficient automatic data analysis, in order to allow a data interpretation as independent as possible from any a priori knowledge. This paper describes the post-processing application of a kind of neural network (self-organizing map, SOM) to the identification of the fundamental HVSR frequency of a given site. SOM results can be represented as two-dimensional maps, with a non-parametric mapping that projects the high dimensional original dataset in a fashion that provides both an unsupervised clustering and a highly visual representation of the data relationships. This innovative application of the SOM algorithm is presented with a case study related to the characterization of a mineral deposit.
Improvement of HVSR technique by self-organizing map (SOM) analysis
Carniel, Roberto (Autor:in) / Barbui, Luca (Autor:in) / Malisan, Petra (Autor:in)
Soil Dynamics and Earthquake Engineering ; 29 ; 1097-1101
14.11.2008
5 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Improvement of HVSR technique by self-organizing map (SOM) analysis
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Improvement of HVSR technique by self-organizing map (SOM) analysis
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