Peak ground acceleration prediction by fuzzy logic modeling for Iranian plateau

Karimi Ghalehjough, Babak; Mahinroosta, Reza

doi:10.1007/s11600-019-00394-z

Artykuł - szczegóły

Tytuł artykułu

Peak ground acceleration prediction by fuzzy logic modeling for Iranian plateau

Autorzy

Karimi Ghalehjough Babak , Mahinroosta Reza

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Identyfikatory

DOI

10.1007/s11600-019-00394-z

Warianty tytułu

Języki publikacji

Abstrakty

In this study, fuzzy logic modeling is applied to a complex and nonlinear set of data to predict both horizontal and vertical peak ground accelerations in Iranian plateau. The data used for the model include an up-to-date seismic catalogue from earthquakes in Iran for prediction of both horizontal and vertical acceleration of a probable earthquake. Fuzzy logic toolbox on MATLAB program was used for modeling. Earthquake magnitude ranging from 4 to 7.4, source-to-site distance from 7 to 80 km and three diferent site conditions were considered: rock, stif soil and soft soil. Results are compared with those from worldwide and regional attenuation relationships, which show the higher capability of the model in comparison with the other models. After training the model, testing of the fuzzy model with the remaining data set was performed to confrm the accuracy of the model. Changes in the peak ground accelerations in connection with changes in input parameters are studied which are in agreement with basic characteristics of earthquake input motions.

Słowa kluczowe

fuzzy logic modeling attenuation relationship peak ground acceleration earthquake input motion

modelowanie rozmyte relacja tłumienia

Wydawca

Instytut Geofizyki PAN
Springer

Czasopismo

Acta Geophysica

Rocznik

2020

Tom

Vol. 68, no. 1

Strony

75--89

Opis fizyczny

Bibliogr. 55 poz.

Twórcy

autor

Karimi Ghalehjough Babak

karimi.babak@gmail.com

Civil Engineering Department, Erzurum Technical University, Room: K1-08, 25050 Erzurum, Turkey

autor

Mahinroosta Reza

rmahinroosta@csu.edu.au

CSU Engineering, Faculty of Business, Justice and Behavioral Sciences, Charles Sturt University, Panorama Avenue, Bathurst, NSW 2795, Australia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021)

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-529b4468-86a5-428c-9527-c6cec5dc2feb