| 基于小波分析和神经网络的静力触探土类划分 |
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| 引用本文： | 彭俊伟.基于小波分析和神经网络的静力触探土类划分[J].工业建筑,2009(Z1). |
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| 作者姓名： | 彭俊伟 |
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| 作者单位： | 中铁第四勘察设计院集团有限公司; |
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| 摘 要： | 利用小波分析和BP神经网络,建立一种用于基于静力触探数据进行土类划分的神经网络模型。该方法基于实测数据,利用小波分析获得不同土层触探参数的特征值,并用BP神经网络建立特征值与土类之间的映射关系,从而得到BP神经网络分类模型。结果表明,该方法可以有效地进行土类划分。
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| 关 键 词： | 静力触探 小波分析 BP神经网络 土类划分 |
STUDY ON SOILS DIVIDED BY STATIC CONE PENETRATION PARAMETERS BASED ON WAVELET ANALYSIS AND ARTIFICIAL NEURAL NETWORK |
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| Peng Junwei.STUDY ON SOILS DIVIDED BY STATIC CONE PENETRATION PARAMETERS BASED ON WAVELET ANALYSIS AND ARTIFICIAL NEURAL NETWORK[J].Industrial Construction,2009(Z1). |
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| Authors: | Peng Junwei |
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| Affiliation: | China Railway Siyuan Survey and Design Group Co.;Ltd.Wuhan;430063;China |
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| Abstract: | The model of soils divided by static cone penetration parameters is built by wavelet analysis and artificial neural network.The characteristic values which are used to gain the BP artificial neural network are from the measured data by wavelet analysis,and BP artificial neural network is used to establish the mapping relation of the characteristic values and soil type.Thus,a classification model of BP artificial neural network is built.The study shows that this method is effective for soil division,and the ... |
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| Keywords: | static cone penetration wavelet analysis BP artificial neural network soil division |
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