TY - JOUR
T1 - Application of adaptive neuro-fuzzy inference system for prediction of internal stability of soils
AU - Xue, Xinhua
AU - Xiao, Ming
N1 - Publisher Copyright:
© 2016, © 2016 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2019/2/1
Y1 - 2019/2/1
N2 - This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for the assessment of internal stability of soils under seepage. The training of fuzzy system was performed by a hybrid method of back-propagation (BP) and least mean square algorithm, and the subtractive clustering algorithm was utilised for optimising the number of fuzzy rules. Experimental data on internal stability of soils in the literature were used to validate and evaluate the performance of the proposed ANFIS model. Further, predictions from three models (the BP model, the particle swarm optimisation-BP model and the ANFIS model) were compared with the experimental data. The results show that the ANFIS model is a feasible, efficient and accurate tool for predicting the internal stability of soils according to Wan and Fell’s criterion.
AB - This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for the assessment of internal stability of soils under seepage. The training of fuzzy system was performed by a hybrid method of back-propagation (BP) and least mean square algorithm, and the subtractive clustering algorithm was utilised for optimising the number of fuzzy rules. Experimental data on internal stability of soils in the literature were used to validate and evaluate the performance of the proposed ANFIS model. Further, predictions from three models (the BP model, the particle swarm optimisation-BP model and the ANFIS model) were compared with the experimental data. The results show that the ANFIS model is a feasible, efficient and accurate tool for predicting the internal stability of soils according to Wan and Fell’s criterion.
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U2 - 10.1080/19648189.2016.1271363
DO - 10.1080/19648189.2016.1271363
M3 - Article
AN - SCOPUS:85007089973
SN - 1964-8189
VL - 23
SP - 153
EP - 171
JO - European Journal of Environmental and Civil Engineering
JF - European Journal of Environmental and Civil Engineering
IS - 2
ER -