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

被引：7
|
作者：
Vatanshenas, Ali [1 ]
Lansivaara, Tim Tapani [1 ]
机构：
[1] Tampere Univ, Fac Built Environm, Korkeakoulunkatu 5, Tampere 33720, Finland
来源：
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING | 2022年 / 153卷
关键词：
Anfis; Fuzzy sets; Shear modulus; Soil dynamics; Very small strain; LOGIC; STIFFNESS;
D O I：
10.1016/j.soildyn.2021.107105
中图分类号：
P5 [地质学];
学科分类号：
0709 ; 081803 ;
摘要：
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.
引用
收藏
页数：5
相关论文
共 50 条
  • [1] Estimating maximum shear modulus (G0) using adaptive neuro-fuzzy inference system (ANFIS)
    Vatanshenas, Ali
    Länsivaara, Tim Tapani
    Soil Dynamics and Earthquake Engineering, 2022, 153
  • [2] LANDSLIDE SUSCEPTIBILITY MAPPING BY USING AN ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS)
    Choi, J.
    Lee, Y. K.
    Lee, M. J.
    Kim, K.
    Park, Y.
    Kim, S.
    Goo, S.
    Cho, M.
    Sim, J.
    Won, J. S.
    2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2011, : 1989 - 1992
  • [3] Prediction of concrete elastic modulus using adaptive neuro-fuzzy inference system
    Aydin, Abdulkadir Cueneyt
    Tortum, Ahmet
    Yavuz, Murat
    CIVIL ENGINEERING AND ENVIRONMENTAL SYSTEMS, 2006, 23 (04) : 295 - 309
  • [4] Optimization of Photosynthetic Rate Parameters using Adaptive Neuro-Fuzzy Inference System (ANFIS)
    Valenzuela, Ira C.
    Baldovino, Renann G.
    Bandala, Argel A.
    Dadios, Elmer P.
    2017 INTERNATIONAL CONFERENCE ON COMPUTER AND APPLICATIONS (ICCA), 2017, : 129 - 134
  • [5] ESTIMATION OF SUBSURFACE STRATA OF EARTH USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS)
    Srinivas, Y.
    Raj, A. Stanley
    Oliver, D. Hudson
    Muthuraj, D.
    Chandrasekar, N.
    ACTA GEODAETICA ET GEOPHYSICA HUNGARICA, 2012, 47 (01): : 78 - 89
  • [6] Estimation of wind speed profile using adaptive neuro-fuzzy inference system (ANFIS)
    Mohandes, M.
    Rehman, S.
    Rahman, S. M.
    APPLIED ENERGY, 2011, 88 (11) : 4024 - 4032
  • [7] Detection Of Forearm Movements Using Wavelets And Adaptive Neuro-Fuzzy Inference System (ANFIS)
    Guvenc, Seyit Ahmet
    Demir, Mengu
    Ulutas, Mustafa
    2014 IEEE INTERNATIONAL SYMPOSIUM ON INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS (INISTA 2014), 2014, : 192 - 196
  • [8] Estimation of subsurface strata of earth using Adaptive Neuro-Fuzzy Inference System (ANFIS)
    Y. Srinivas
    A. Stanley Raj
    D. Hudson Oliver
    D. Muthuraj
    N. Chandrasekar
    Acta Geodaetica et Geophysica Hungarica, 2012, 47 : 78 - 89
  • [9] Prediction of FRP shear contribution for wrapped shear deficient RC beams using adaptive neuro-fuzzy inference system (ANFIS)
    Kar, Swapnasarit
    Pandit, Amiya R.
    Biswal, K. C.
    STRUCTURES, 2020, 23 : 702 - 717
  • [10] Discharge predicted in compound channels using adaptive neuro-fuzzy inference system (ANFIS)
    Khattab, Noor I. I.
    Mohammed, Ahmed Y. Y.
    Mala Obaida, Arwa A. A.
    OPEN ENGINEERING, 2023, 13 (01):
12345