| 膨胀土胀缩等级的SOM神经网络评判及验证 |
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| 引用本文： | 鲍灵高,梁翔.膨胀土胀缩等级的SOM神经网络评判及验证[J].重庆交通大学学报(自然科学版),2009,28(1):84-89. |
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| 作者姓名： | 鲍灵高 梁翔 |
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| 作者单位： | 1. 贵州省桥梁工程总公司,贵州,贵阳,550001
2. 机械工业第三设计院市政交通院,重庆,400039 |
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| 摘 要： | 在对现有膨胀土判别分类方法进行评价的基础上,根据公路建设中的常规试验项目选择了液限、塑性指数、小于0.002 mm的黏粒含量、CBR、自由膨胀率和CBR膨胀率6项指标,通过确定每项指标的界限值,建立了以神经网络中的SOM网络模型为理论依据的膨胀土胀缩等级评判模型,编写了评判软件;并应用评判模型对沿线膨胀土土样的胀缩等级进行了评判分类;通过应用膨胀土土样6项指标以外的胀缩性能和强度性能指标进行验证,证明了分类结果是正确可靠的。
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| 关 键 词： | 膨胀土 胀缩等级 SOM神经网络 试验验证 |
SOM Neural Network Judgment and Validation on Swelling and Shrinking Grade of Expansive Soil |
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| BAO Ling-gao,LIANG Xiang.SOM Neural Network Judgment and Validation on Swelling and Shrinking Grade of Expansive Soil[J].Journal of Chongqing Jiaotong University,2009,28(1):84-89. |
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| Authors: | BAO Ling-gao LIANG Xiang |
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| Institution: | 1.Guizhou Provincial Bridge Engineering Group;Guizhou Guiyang 550001;China;2.Institute of Municipal Traffic;Third Design & Research Institute of Mechanical Industry;Chongqing 400039;China |
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| Abstract: | The existing approaches to identify and classify expansive soil have been evaluated.The indices that can reflect and characterize the swell-shrink mechanism and properties are analyzed.Making use of six indices such as liquid limit,plasticity index,less than two microns glutinous granule percent,CBR,free expansion ratio and CBR expansion ratio,the swelling and shrinking grade model on the theoretic base of SOM neural network model is established through determining the limit value of every index.And the jud... |
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| Keywords: | expansive soil grade of expansion and shrink SOM neural network experimental validation |
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