[1]李志刚,邓学钧,陈云鹤,等.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.[doi:10.3969/j.issn.1001-0505.2002.06.030]
 Li Zhigang,Deng Xuejun,Chen Yunhe,et al.Simulated calculation of highway slope erosion based on artificial neural networks[J].Journal of Southeast University (Natural Science Edition),2002,32(6):960-963.[doi:10.3969/j.issn.1001-0505.2002.06.030]
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基于神经网络的公路边坡冲刷量模拟计算()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
32
期数:
2002年第6期
页码:
960-963
栏目:
交通运输工程
出版日期:
2002-11-20

文章信息/Info

Title:
Simulated calculation of highway slope erosion based on artificial neural networks
作者:
李志刚12 邓学钧2 陈云鹤1 洪锋2
1 解放军理工大学工程兵工程学院,南京 210007; 2 东南大学交通学院, 南京 210096
Author(s):
Li Zhigang12 Deng Xuejun2 Chen Yunhe1 Hong Feng2
1 Engineering Institute of Engineering Corps, PLA University of Science and Technology, Nanjing 210007, China
2 Transportation College, Southeast University, Nanjing 210096, China
关键词:
公路边坡 冲刷量 人工神经网络 BP算法
Keywords:
highway slope erosion ANN BP algorithm
分类号:
U416.1
DOI:
10.3969/j.issn.1001-0505.2002.06.030
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30 min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.
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.

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备注/Memo

备注/Memo:
作者简介: 李志刚(1972—),男,博士后,讲师.
更新日期/Last Update: 2002-11-20