TY - JOUR
T1 - A fuzzy neural network approach to evaluation of slope failure potential
AU - Ni, S. H.
AU - Lu, P. C.
AU - Juang, C. H.
PY - 1996
Y1 - 1996
N2 - Stability of natural slopes depends highly on their existing geologic conditions and surrounding environment. However, the conditions of a natural slope and its environment usually cannot be described with precise numbers. Thus an approach that is capable of dealing with vagueness in the stability evaluation of natural slopes is essential. This paper presents a fuzzy neural network approach for evaluating the stability of natural slopes. In this approach, fuzzy sets are used to represent the parameters of the neural network. A total of 13 factors that are believed to be important to the stability of natural slopes are used as input parameters. A two-stage training method is used for establishing fuzzy parameters. A fuzzy artificial neural network is developed and tested. A number of hypothetical natural slopes are evaluated, and the results appear to be reasonable compared with those obtained by different approaches in a previous study.
AB - Stability of natural slopes depends highly on their existing geologic conditions and surrounding environment. However, the conditions of a natural slope and its environment usually cannot be described with precise numbers. Thus an approach that is capable of dealing with vagueness in the stability evaluation of natural slopes is essential. This paper presents a fuzzy neural network approach for evaluating the stability of natural slopes. In this approach, fuzzy sets are used to represent the parameters of the neural network. A total of 13 factors that are believed to be important to the stability of natural slopes are used as input parameters. A two-stage training method is used for establishing fuzzy parameters. A fuzzy artificial neural network is developed and tested. A number of hypothetical natural slopes are evaluated, and the results appear to be reasonable compared with those obtained by different approaches in a previous study.
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U2 - 10.1111/j.1467-8667.1996.tb00309.x
DO - 10.1111/j.1467-8667.1996.tb00309.x
M3 - Article
AN - SCOPUS:19944397551
SN - 1093-9687
VL - 11
SP - 59
EP - 66
JO - Computer-Aided Civil and Infrastructure Engineering
JF - Computer-Aided Civil and Infrastructure Engineering
IS - 1
ER -