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首页> 外文期刊>Applied Soft Computing >Prediction of scouring around an arch-shaped bed sill using Neuro-Fuzzy model
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Prediction of scouring around an arch-shaped bed sill using Neuro-Fuzzy model

机译：使用Neuro-Fuzzy模型预测拱形床槛周围的冲刷

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In this study, Adaptive Neuro-Fuzzy Inference System (ANFIS) has been used to model local scouring depth and pattern scouring around concave and convex arch shaped circular bed sills. The experimental part of this research study includes seven sets of laboratory test cases which were performed in an experimental flume under different flow conditions. A data set consists of 2754 data points of scouring depth were collected to use in the ANFIS model. The ratio of arch diameter, D, to flume width, W, is used as a non dimensional variables in all test cases. The results from ANFIS model were compared with the results of ANN model obtained by Homayoon et al. [24] and previously presented models. The results indicated that for D/W equal to 1 and 1.2, the ANFIS models produced a good performance for convex and concave bed sills. As a result, the ANFIS models can be used as an alternative to ANN for estimation of scour depth and scour pattern around a concave bed sill installed with a bridge pier.
机译：在这项研究中，自适应神经模糊推理系统（ANFIS）已被用来模拟凹面和凸面拱形圆形底台周围的局部冲刷深度和图案冲刷。本研究的实验部分包括七组实验室测试用例，它们是在不同流量条件下的实验水槽中进行的。收集了一个包含2754个冲刷深度数据点的数据集，以用于ANFIS模型。在所有测试案例中，圆弧直径D与水槽宽度W的比均用作无量纲变量。将ANFIS模型的结果与Homayoon等人获得的ANN模型的结果进行比较。 [24]和先前介绍的模型。结果表明，当D / W等于1和1.2时，ANFIS模型对于凸凹底梁具有良好的性能。因此，可以将ANFIS模型用作ANN的替代方法，以估计安装有桥墩的凹床槛周围的冲刷深度和冲刷模式。

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