| 融沉系数的人工神经网络预测方法 |
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| 引用本文： | 姚晓亮,齐吉琳.融沉系数的人工神经网络预测方法[J].冰川冻土,2011,33(4):891-896. |
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| 作者姓名： | 姚晓亮 齐吉琳 |
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| 作者单位： | 中国科学院寒区旱区环境与工程研究所冻土工程国家重点实验室,甘肃兰州,730000 |
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| 基金项目： | 中国科学院冻土工程国家重点实验室自主课题“冻土融化固结试验与理论研究”(2010)资助 |
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| 摘 要： | 分析了前人关于融沉系数经验方法的研究结果，结果显示，与融沉系数关系最为密切的物性参数为液塑限、粉黏粒含量、干密度和含水量（含冰量）．为了能够综合描述诸因素与融沉系数的经验关系，以兰州黄土和青藏黏土为试验对象，得到了两种具有不同物性参数的土在不同含水量和干密度条件下的融沉系数．采用BP神经网络算法对试验数据进行学习训练，...
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| 关 键 词： | 融沉系数 人工神经网络 物性参数 干密度 含水量 |
Artificial Neural Network Forecasting Method for Thaw-Settlement Coefficient |
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| YAO Xiao-liang,QI Ji-lin.Artificial Neural Network Forecasting Method for Thaw-Settlement Coefficient[J].Journal of Glaciology and Geocryology,2011,33(4):891-896. |
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| Authors: | YAO Xiao-liang QI Ji-lin |
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| Institution: | YAO Xiao-liang,QI Ji-lin(State Key Laboratory o f Frozen Soil Engineering,Cold and Arid Regions Environmental and EngineeringResearch Institute,Chinese Academy Sciences,Lanzhou Gansu 730000,China) |
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| Abstract: | Thaw-settlement is a tranditional issue in frozen soil mechanics and engineering,but so far yet there is not a widely accepted forecasting method for the thaw-settlement coefficient.Through analyzing the previous study achievement on empirical method,in this paper,Atterberg Limits,fine particles content,dry unit weight and water content are proposed to be the indexes that closely relates to thaw-settlement coefficient.In order to describe the relationship between all those factors and thaw-settlement coeffi... |
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| Keywords: | thaw-settlement coefficient artificial neural network physical parameters dry unit weight water content |
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