It shows that the neural networks and neuro-fuzzy approaches predict scour depth much more accurately than the existing methods. It also includes the�...
Estimation of equilibrium and time-dependent depth of local scour around bridge piers is a vital issue in the design of bridges. Various design methods and�...
Numerical tests indicate that MLP/BP model provide a better prediction of scour depth than RBF/OLS and ANFIS models as well as the previous empirical approaches�...
Sharif Digital Repository / Sharif University of Technology - Neural network and neuro-fuzzy assessments for scour depth around bridge piers,Author: Bateni, S.
In this study, alternative approaches, artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS), are proposed to estimate the�...
Jeng et al (2005) employed an artificial neural network to predict equilibrium scour depth and time-dependent scour depth. They developed two Bayesian models�...
It was found that the ANN with two hidden layers was the optimum model to predict local scour depth. The results from the sixth test case showed that the ANN�...
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This paper describes the use of an adaptive neuro-fuzzy inference system (ANFIS) and a Gamma Test (GT) to estimate the submerged pipeline scour depth. The data�...
They observed that the neural net- works and neuro-fuzzy approaches predict scour depth much more precisely than the present methods, especially multilayer�...
May 31, 2024 � ... Neuro-Fuzzy Inference Systems (ANFIS), and ... neural networks in assessing the equilibrium depth of local scour around bridge piers.