Peak Ground Velocity attenuation relationships using Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{Kermani:2019:ICEGE,
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author = "E. Kermani and S. Barzegari and Y. Jafarian and
M. H. Baziar",
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title = "Peak Ground Velocity attenuation relationships using
Genetic Programming",
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booktitle = "Earthquake Geotechnical Engineering for Protection and
Development of Environment and Constructions",
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year = "2019",
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editor = "Silvestri and Moraci",
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pages = "3269--3276",
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address = "Rome, Italy",
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publisher = "Associazione Geotecnica Italiana",
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note = "TC203",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-0-367-14328-2",
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URL = "https://www.geoengineer.org/publications/online-library?keywords=A&page=1481",
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URL = "https://www.issmge.org/uploads/publications/59/104/ch347.pdf",
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size = "8 pages",
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abstract = "Peak Ground Velocity (PGV) is one of the most
important ground motion parameters that has been widely
used as a damage potential indicator, as well as in
seismic design of structures and assessment of buried
pipelines and liquefaction potential analysis.
Therefore, estimating a precise value for this
parameter is of great importance. Genetic Programming
(GP), a well-known Artificial Intelligence method is
used to develop an attenuation relationship for PGV
based on the strong ground motion database released by
Pacific Earthquake Engineering Research center (PEER).
Different PGV attenuation relation-ships are proposed
for strike-slip, normal, and reverse faulting
mechanisms as functions of earthquake magnitude, source
to site distance, and local site geotechnical
condition. The values of coefficient of determination,
root mean square error and mean absolute error are
calculated for the developed PGV attenuation
relationships and reveal the accuracy of proposed
model. Results of the parametric study demonstrate that
PGV is higher for larger earth-quake magnitudes while
it is lower for sites which are located farther from
the source and have lower shear wave velocities.",
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notes = "p3276 'comparison with the other PGV attenuation
relationships in literature demonstrates the superior
performance of the proposed GP models'
7th International Conference on Earthquake Geotechnical
Engineering
Pennsylvania State University, USA",
- }
Genetic Programming entries for
Elnaz Kermani
Saman Barzegari
Yaser Jafarian
Mohammad Hassan Baziar
Citations