K-means for earthquakes: disaggregation analyses of small events by considering wave components and soil types
Abstract In this paper, k-means algorithm has been used to disaggregate seismic parameters to evaluate their inter-correlations. A goal is to quantify in a disaggregated way the weights and effects of each parameter with respect to other ones. From the database, about 4900.0 data, divided into 22.0...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zacchei, Enrico [verfasserIn] Brasil, Reyolando [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2024 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2024 |
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| Übergeordnetes Werk: |
Enthalten in: Arabian journal of geosciences - Springer International Publishing, 2008, 17(2024), 11 vom: 21. Okt. |
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| Übergeordnetes Werk: |
volume:17 ; year:2024 ; number:11 ; day:21 ; month:10 |
| Links: |
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| DOI / URN: |
10.1007/s12517-024-12113-0 |
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| Katalog-ID: |
SPR057935661 |
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| 520 | |a Abstract In this paper, k-means algorithm has been used to disaggregate seismic parameters to evaluate their inter-correlations. A goal is to quantify in a disaggregated way the weights and effects of each parameter with respect to other ones. From the database, about 4900.0 data, divided into 22.0 categories, have been collected. The main divisions regard the wave components in horizontal and vertical axis and the soil characteristics. The studied seismic zone is the “Norpirenaica oriental,” placed in the Pyrenees area between Spain and France, classified as a very high seismic hazard. Numerical and analytical analyses have been carried out to implement the algorithm. Preliminary analyses and results would quantify the role of the sand horizontal stratigraphy, the non-linear effects, the elasticity of the soil, and the energy damping phenomenon. Curves are plotted in stochastic distributions and elastic spectra accelerations. Results show good prediction for vertical spectral accelerations and for far and relative strong events. Rigorously, results are valid only for the studied seismogenic zone under predefined constrictions and ranges. | ||
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10.1007/s12517-024-12113-0 doi (DE-627)SPR057935661 (SPR)s12517-024-12113-0-e DE-627 ger DE-627 rakwb eng 550 VZ Zacchei, Enrico verfasserin aut K-means for earthquakes: disaggregation analyses of small events by considering wave components and soil types 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract In this paper, k-means algorithm has been used to disaggregate seismic parameters to evaluate their inter-correlations. A goal is to quantify in a disaggregated way the weights and effects of each parameter with respect to other ones. From the database, about 4900.0 data, divided into 22.0 categories, have been collected. The main divisions regard the wave components in horizontal and vertical axis and the soil characteristics. The studied seismic zone is the “Norpirenaica oriental,” placed in the Pyrenees area between Spain and France, classified as a very high seismic hazard. Numerical and analytical analyses have been carried out to implement the algorithm. Preliminary analyses and results would quantify the role of the sand horizontal stratigraphy, the non-linear effects, the elasticity of the soil, and the energy damping phenomenon. Curves are plotted in stochastic distributions and elastic spectra accelerations. Results show good prediction for vertical spectral accelerations and for far and relative strong events. Rigorously, results are valid only for the studied seismogenic zone under predefined constrictions and ranges. AI (dpeaa)DE-He213 K-means (dpeaa)DE-He213 Disaggregation analyses (dpeaa)DE-He213 Pyrenees area (dpeaa)DE-He213 Seismic analyses (dpeaa)DE-He213 Brasil, Reyolando verfasserin aut Enthalten in Arabian journal of geosciences Springer International Publishing, 2008 17(2024), 11 vom: 21. Okt. (DE-627)572421877 (DE-600)2438771-X 1866-7538 nnns volume:17 year:2024 number:11 day:21 month:10 https://dx.doi.org/10.1007/s12517-024-12113-0 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 17 2024 11 21 10 |
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10.1007/s12517-024-12113-0 doi (DE-627)SPR057935661 (SPR)s12517-024-12113-0-e DE-627 ger DE-627 rakwb eng 550 VZ Zacchei, Enrico verfasserin aut K-means for earthquakes: disaggregation analyses of small events by considering wave components and soil types 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract In this paper, k-means algorithm has been used to disaggregate seismic parameters to evaluate their inter-correlations. A goal is to quantify in a disaggregated way the weights and effects of each parameter with respect to other ones. From the database, about 4900.0 data, divided into 22.0 categories, have been collected. The main divisions regard the wave components in horizontal and vertical axis and the soil characteristics. The studied seismic zone is the “Norpirenaica oriental,” placed in the Pyrenees area between Spain and France, classified as a very high seismic hazard. Numerical and analytical analyses have been carried out to implement the algorithm. Preliminary analyses and results would quantify the role of the sand horizontal stratigraphy, the non-linear effects, the elasticity of the soil, and the energy damping phenomenon. Curves are plotted in stochastic distributions and elastic spectra accelerations. Results show good prediction for vertical spectral accelerations and for far and relative strong events. Rigorously, results are valid only for the studied seismogenic zone under predefined constrictions and ranges. AI (dpeaa)DE-He213 K-means (dpeaa)DE-He213 Disaggregation analyses (dpeaa)DE-He213 Pyrenees area (dpeaa)DE-He213 Seismic analyses (dpeaa)DE-He213 Brasil, Reyolando verfasserin aut Enthalten in Arabian journal of geosciences Springer International Publishing, 2008 17(2024), 11 vom: 21. Okt. (DE-627)572421877 (DE-600)2438771-X 1866-7538 nnns volume:17 year:2024 number:11 day:21 month:10 https://dx.doi.org/10.1007/s12517-024-12113-0 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 17 2024 11 21 10 |
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10.1007/s12517-024-12113-0 doi (DE-627)SPR057935661 (SPR)s12517-024-12113-0-e DE-627 ger DE-627 rakwb eng 550 VZ Zacchei, Enrico verfasserin aut K-means for earthquakes: disaggregation analyses of small events by considering wave components and soil types 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract In this paper, k-means algorithm has been used to disaggregate seismic parameters to evaluate their inter-correlations. A goal is to quantify in a disaggregated way the weights and effects of each parameter with respect to other ones. From the database, about 4900.0 data, divided into 22.0 categories, have been collected. The main divisions regard the wave components in horizontal and vertical axis and the soil characteristics. The studied seismic zone is the “Norpirenaica oriental,” placed in the Pyrenees area between Spain and France, classified as a very high seismic hazard. Numerical and analytical analyses have been carried out to implement the algorithm. Preliminary analyses and results would quantify the role of the sand horizontal stratigraphy, the non-linear effects, the elasticity of the soil, and the energy damping phenomenon. Curves are plotted in stochastic distributions and elastic spectra accelerations. Results show good prediction for vertical spectral accelerations and for far and relative strong events. Rigorously, results are valid only for the studied seismogenic zone under predefined constrictions and ranges. AI (dpeaa)DE-He213 K-means (dpeaa)DE-He213 Disaggregation analyses (dpeaa)DE-He213 Pyrenees area (dpeaa)DE-He213 Seismic analyses (dpeaa)DE-He213 Brasil, Reyolando verfasserin aut Enthalten in Arabian journal of geosciences Springer International Publishing, 2008 17(2024), 11 vom: 21. Okt. (DE-627)572421877 (DE-600)2438771-X 1866-7538 nnns volume:17 year:2024 number:11 day:21 month:10 https://dx.doi.org/10.1007/s12517-024-12113-0 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 17 2024 11 21 10 |
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10.1007/s12517-024-12113-0 doi (DE-627)SPR057935661 (SPR)s12517-024-12113-0-e DE-627 ger DE-627 rakwb eng 550 VZ Zacchei, Enrico verfasserin aut K-means for earthquakes: disaggregation analyses of small events by considering wave components and soil types 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract In this paper, k-means algorithm has been used to disaggregate seismic parameters to evaluate their inter-correlations. A goal is to quantify in a disaggregated way the weights and effects of each parameter with respect to other ones. From the database, about 4900.0 data, divided into 22.0 categories, have been collected. The main divisions regard the wave components in horizontal and vertical axis and the soil characteristics. The studied seismic zone is the “Norpirenaica oriental,” placed in the Pyrenees area between Spain and France, classified as a very high seismic hazard. Numerical and analytical analyses have been carried out to implement the algorithm. Preliminary analyses and results would quantify the role of the sand horizontal stratigraphy, the non-linear effects, the elasticity of the soil, and the energy damping phenomenon. Curves are plotted in stochastic distributions and elastic spectra accelerations. Results show good prediction for vertical spectral accelerations and for far and relative strong events. Rigorously, results are valid only for the studied seismogenic zone under predefined constrictions and ranges. AI (dpeaa)DE-He213 K-means (dpeaa)DE-He213 Disaggregation analyses (dpeaa)DE-He213 Pyrenees area (dpeaa)DE-He213 Seismic analyses (dpeaa)DE-He213 Brasil, Reyolando verfasserin aut Enthalten in Arabian journal of geosciences Springer International Publishing, 2008 17(2024), 11 vom: 21. Okt. (DE-627)572421877 (DE-600)2438771-X 1866-7538 nnns volume:17 year:2024 number:11 day:21 month:10 https://dx.doi.org/10.1007/s12517-024-12113-0 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 17 2024 11 21 10 |
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10.1007/s12517-024-12113-0 doi (DE-627)SPR057935661 (SPR)s12517-024-12113-0-e DE-627 ger DE-627 rakwb eng 550 VZ Zacchei, Enrico verfasserin aut K-means for earthquakes: disaggregation analyses of small events by considering wave components and soil types 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract In this paper, k-means algorithm has been used to disaggregate seismic parameters to evaluate their inter-correlations. A goal is to quantify in a disaggregated way the weights and effects of each parameter with respect to other ones. From the database, about 4900.0 data, divided into 22.0 categories, have been collected. The main divisions regard the wave components in horizontal and vertical axis and the soil characteristics. The studied seismic zone is the “Norpirenaica oriental,” placed in the Pyrenees area between Spain and France, classified as a very high seismic hazard. Numerical and analytical analyses have been carried out to implement the algorithm. Preliminary analyses and results would quantify the role of the sand horizontal stratigraphy, the non-linear effects, the elasticity of the soil, and the energy damping phenomenon. Curves are plotted in stochastic distributions and elastic spectra accelerations. Results show good prediction for vertical spectral accelerations and for far and relative strong events. Rigorously, results are valid only for the studied seismogenic zone under predefined constrictions and ranges. AI (dpeaa)DE-He213 K-means (dpeaa)DE-He213 Disaggregation analyses (dpeaa)DE-He213 Pyrenees area (dpeaa)DE-He213 Seismic analyses (dpeaa)DE-He213 Brasil, Reyolando verfasserin aut Enthalten in Arabian journal of geosciences Springer International Publishing, 2008 17(2024), 11 vom: 21. Okt. (DE-627)572421877 (DE-600)2438771-X 1866-7538 nnns volume:17 year:2024 number:11 day:21 month:10 https://dx.doi.org/10.1007/s12517-024-12113-0 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 17 2024 11 21 10 |
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A goal is to quantify in a disaggregated way the weights and effects of each parameter with respect to other ones. From the database, about 4900.0 data, divided into 22.0 categories, have been collected. The main divisions regard the wave components in horizontal and vertical axis and the soil characteristics. The studied seismic zone is the “Norpirenaica oriental,” placed in the Pyrenees area between Spain and France, classified as a very high seismic hazard. Numerical and analytical analyses have been carried out to implement the algorithm. Preliminary analyses and results would quantify the role of the sand horizontal stratigraphy, the non-linear effects, the elasticity of the soil, and the energy damping phenomenon. Curves are plotted in stochastic distributions and elastic spectra accelerations. Results show good prediction for vertical spectral accelerations and for far and relative strong events. 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Zacchei, Enrico |
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Zacchei, Enrico ddc 550 misc AI misc K-means misc Disaggregation analyses misc Pyrenees area misc Seismic analyses K-means for earthquakes: disaggregation analyses of small events by considering wave components and soil types |
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550 VZ K-means for earthquakes: disaggregation analyses of small events by considering wave components and soil types AI (dpeaa)DE-He213 K-means (dpeaa)DE-He213 Disaggregation analyses (dpeaa)DE-He213 Pyrenees area (dpeaa)DE-He213 Seismic analyses (dpeaa)DE-He213 |
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K-means for earthquakes: disaggregation analyses of small events by considering wave components and soil types |
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k-means for earthquakes: disaggregation analyses of small events by considering wave components and soil types |
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K-means for earthquakes: disaggregation analyses of small events by considering wave components and soil types |
| abstract |
Abstract In this paper, k-means algorithm has been used to disaggregate seismic parameters to evaluate their inter-correlations. A goal is to quantify in a disaggregated way the weights and effects of each parameter with respect to other ones. From the database, about 4900.0 data, divided into 22.0 categories, have been collected. The main divisions regard the wave components in horizontal and vertical axis and the soil characteristics. The studied seismic zone is the “Norpirenaica oriental,” placed in the Pyrenees area between Spain and France, classified as a very high seismic hazard. Numerical and analytical analyses have been carried out to implement the algorithm. Preliminary analyses and results would quantify the role of the sand horizontal stratigraphy, the non-linear effects, the elasticity of the soil, and the energy damping phenomenon. Curves are plotted in stochastic distributions and elastic spectra accelerations. Results show good prediction for vertical spectral accelerations and for far and relative strong events. Rigorously, results are valid only for the studied seismogenic zone under predefined constrictions and ranges. © The Author(s) 2024 |
| abstractGer |
Abstract In this paper, k-means algorithm has been used to disaggregate seismic parameters to evaluate their inter-correlations. A goal is to quantify in a disaggregated way the weights and effects of each parameter with respect to other ones. From the database, about 4900.0 data, divided into 22.0 categories, have been collected. The main divisions regard the wave components in horizontal and vertical axis and the soil characteristics. The studied seismic zone is the “Norpirenaica oriental,” placed in the Pyrenees area between Spain and France, classified as a very high seismic hazard. Numerical and analytical analyses have been carried out to implement the algorithm. Preliminary analyses and results would quantify the role of the sand horizontal stratigraphy, the non-linear effects, the elasticity of the soil, and the energy damping phenomenon. Curves are plotted in stochastic distributions and elastic spectra accelerations. Results show good prediction for vertical spectral accelerations and for far and relative strong events. Rigorously, results are valid only for the studied seismogenic zone under predefined constrictions and ranges. © The Author(s) 2024 |
| abstract_unstemmed |
Abstract In this paper, k-means algorithm has been used to disaggregate seismic parameters to evaluate their inter-correlations. A goal is to quantify in a disaggregated way the weights and effects of each parameter with respect to other ones. From the database, about 4900.0 data, divided into 22.0 categories, have been collected. The main divisions regard the wave components in horizontal and vertical axis and the soil characteristics. The studied seismic zone is the “Norpirenaica oriental,” placed in the Pyrenees area between Spain and France, classified as a very high seismic hazard. Numerical and analytical analyses have been carried out to implement the algorithm. Preliminary analyses and results would quantify the role of the sand horizontal stratigraphy, the non-linear effects, the elasticity of the soil, and the energy damping phenomenon. Curves are plotted in stochastic distributions and elastic spectra accelerations. Results show good prediction for vertical spectral accelerations and for far and relative strong events. Rigorously, results are valid only for the studied seismogenic zone under predefined constrictions and ranges. © The Author(s) 2024 |
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11 |
| title_short |
K-means for earthquakes: disaggregation analyses of small events by considering wave components and soil types |
| url |
https://dx.doi.org/10.1007/s12517-024-12113-0 |
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Brasil, Reyolando |
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| doi_str |
10.1007/s12517-024-12113-0 |
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2024-10-22T04:51:53.444Z |
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| score |
7.4020586 |