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基于神经网络的公路边坡冲刷量模拟计算
引用本文:李志刚,邓学钧,陈云鹤,洪锋. 基于神经网络的公路边坡冲刷量模拟计算[J]. 东南大学学报(自然科学版), 2002, 32(6): 960-963
作者姓名:李志刚  邓学钧  陈云鹤  洪锋
作者单位:1. 解放军理工大学工程兵工程学院,南京,210007;东南大学交通学院,南京,210096
2. 东南大学交通学院,南京,210096
3. 解放军理工大学工程兵工程学院,南京,210007
摘    要:神经网络模拟采用三层前馈网络模型,输入层有3个结点,分别代表30min降雨强度、降雨历时和降雨量,表示冲刷外因。输出层只有一个结点,代表坡面冲刷量;隐层结点数采用7个,即土压实度、坡度坡长、径流流速、径流流量、土颗粒粘聚力、植被指数和人为干扰等,为影响冲刷量的主要因素。为了验证模型,在连徐高速公路路堤边坡用SR型人工降雨设施进行冲刷试验,得到冲刷量实测资料,将通过模型计算的冲刷量值与之比较,显示了模型具有较好的模拟预测效果。

关 键 词:模拟计算 公路 边坡 冲刷量 人工神经网络 BP算法 三层前馈网络模型 路基工程
文章编号:1001-0505(2002)06-0960-04

Simulated calculation of highway slope erosion based on artificial neural networks
Li Zhigang , Deng Xuejun Chen Yunhe Hong Feng. Simulated calculation of highway slope erosion based on artificial neural networks[J]. Journal of Southeast University(Natural Science Edition), 2002, 32(6): 960-963
Authors:Li Zhigang    Deng Xuejun Chen Yunhe Hong Feng
Affiliation:Li Zhigang 1,2 Deng Xuejun 2 Chen Yunhe 1 Hong Feng 2
Abstract:The model's first layer consists of 3 nodes, respectively representing the 30 minutes raining intensity, duration, and volume as the external factors. The third layer applies one output node, denoting the slope erosion. There are 7 nodes in the hidden layer. They are compaction, slope length and gradient, flow velocity, flow volume, viscidity, vegetation index, and jamming. In order to verify the mode, the SR artificial rainfall simulator was utilized to conduct a series of experiments at Pizhou segment of Lian Xu freeway. The comparison analysis between the data collected in field and simulated by the model showed an ideal forecast effect.
Keywords:highway slope  erosion  ANN  BP algorithm
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