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Estimating maximum shear modulus (G 0) using adaptive neuro-fuzzy inference system (ANFIS)
https://orcid.org/0000-0003-3163-0921
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, G 0. 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 G 0.
Highlights Fuzzy logic is an adequate approach for problems with variability, uncertainty and unsharp boundaries. Adaptive neuro fuzzy inference system (Anfis) is a suitable tool for approximating soil parameters. Anfis gives the flexibility to select trusted databases rather utilizing lengthy formulas validated for specific datasets. Maximum shear modulus is estimated utilizing easily obtainable variables with clear physical meaning.
Estimating maximum shear modulus (G 0) using adaptive neuro-fuzzy inference system (ANFIS)
https://orcid.org/0000-0003-3163-0921
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, G 0. 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 G 0.
Highlights Fuzzy logic is an adequate approach for problems with variability, uncertainty and unsharp boundaries. Adaptive neuro fuzzy inference system (Anfis) is a suitable tool for approximating soil parameters. Anfis gives the flexibility to select trusted databases rather utilizing lengthy formulas validated for specific datasets. Maximum shear modulus is estimated utilizing easily obtainable variables with clear physical meaning.
Estimating maximum shear modulus (G 0) using adaptive neuro-fuzzy inference system (ANFIS)
https://orcid.org/0000-0003-3163-0921
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, G 0. 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 G 0.
Highlights Fuzzy logic is an adequate approach for problems with variability, uncertainty and unsharp boundaries. Adaptive neuro fuzzy inference system (Anfis) is a suitable tool for approximating soil parameters. Anfis gives the flexibility to select trusted databases rather utilizing lengthy formulas validated for specific datasets. Maximum shear modulus is estimated utilizing easily obtainable variables with clear physical meaning.
Estimating maximum shear modulus (G 0) using adaptive neuro-fuzzy inference system (ANFIS)
Vatanshenas, Ali (author) / Länsivaara, Tim Tapani (author)
2021-11-25
Article (Journal)
Electronic Resource
English
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