Estimating maximum shear modulus (G0) using adaptive neuro-fuzzy inference system (ANFIS)

Ali Vatanshenas; Tim Länsivaara

doi:10.1016/j.soildyn.2021.107105

Estimating maximum shear modulus (G0) using adaptive neuro-fuzzy inference system (ANFIS)

Ali Vatanshenas, Tim Länsivaara

Rakennustekniikka

Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu

7 Sitaatiot (Scopus)

9 Lataukset (Pure)

Abstrakti

Realistic estimation of soil behavior is dependent on considering very small and small strain domains. Lengthy formulas proposed in the literature have limited predictive power for estimation of maximum shear modulus, G0. The aim of this study is to overcome this drawback. Theoretical aspects of fuzzy sets and adaptive neuro-fuzzy inference system (Anfis) are presented. Then, Anfis is implemented within a logical platform that adapts itself with available data to estimate and describe G0.

Alkuperäiskieli	Englanti
Artikkeli	107105
Julkaisu	Soil dynamics and earthquake engineering
Vuosikerta	153
Varhainen verkossa julkaisun päivämäärä	3 jouluk. 2021
DOI - pysyväislinkit	https://doi.org/10.1016/j.soildyn.2021.107105
Tila	Julkaistu - helmik. 2022
OKM-julkaisutyyppi	A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

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10.1016/j.soildyn.2021.107105Lisenssi: CC BY

1-s2.0-S0267726121005273-mainFinal published version, 2,92 MBLisenssi: CC BY

https://urn.fi/URN:NBN:fi:tuni-202112078961Lisenssi: CC BY

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title = "Estimating maximum shear modulus (G0) using adaptive neuro-fuzzy inference system (ANFIS)",

abstract = "Realistic estimation of soil behavior is dependent on considering very small and small strain domains. Lengthy formulas proposed in the literature have limited predictive power for estimation of maximum shear modulus, G0. The aim of this study is to overcome this drawback. Theoretical aspects of fuzzy sets and adaptive neuro-fuzzy inference system (Anfis) are presented. Then, Anfis is implemented within a logical platform that adapts itself with available data to estimate and describe G0. ",

keywords = "Anfis, Fuzzy sets, Shear modulus, Soil dynamics, Very small strain",

author = "Ali Vatanshenas and Tim L{\"a}nsivaara",

year = "2022",

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doi = "10.1016/j.soildyn.2021.107105",

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T1 - Estimating maximum shear modulus (G0) using adaptive neuro-fuzzy inference system (ANFIS)

AU - Vatanshenas, Ali

AU - Länsivaara, Tim

PY - 2022/2

Y1 - 2022/2

N2 - Realistic estimation of soil behavior is dependent on considering very small and small strain domains. Lengthy formulas proposed in the literature have limited predictive power for estimation of maximum shear modulus, G0. The aim of this study is to overcome this drawback. Theoretical aspects of fuzzy sets and adaptive neuro-fuzzy inference system (Anfis) are presented. Then, Anfis is implemented within a logical platform that adapts itself with available data to estimate and describe G0.

AB - Realistic estimation of soil behavior is dependent on considering very small and small strain domains. Lengthy formulas proposed in the literature have limited predictive power for estimation of maximum shear modulus, G0. The aim of this study is to overcome this drawback. Theoretical aspects of fuzzy sets and adaptive neuro-fuzzy inference system (Anfis) are presented. Then, Anfis is implemented within a logical platform that adapts itself with available data to estimate and describe G0.

KW - Anfis

KW - Fuzzy sets

KW - Shear modulus

KW - Soil dynamics

KW - Very small strain

U2 - 10.1016/j.soildyn.2021.107105

DO - 10.1016/j.soildyn.2021.107105

M3 - Article

SN - 0267-7261

VL - 153

JO - Soil dynamics and earthquake engineering

JF - Soil dynamics and earthquake engineering

M1 - 107105

ER -

Estimating maximum shear modulus (G0) using adaptive neuro-fuzzy inference system (ANFIS)

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