An evolutionary neural network model for suction prediction of unsaturated soils

ZHANG Chuan-qing; YANG Qing; LUAN Mao-tian

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An evolutionary neural network model for suction prediction of unsaturated soils

更新时间：2026-06-25

- An evolutionary neural network model for suction prediction of unsaturated soils
- Vol. 25, Issue 1, (2004)
- 作者机构：
  
  大连理工大学土木水利学院及海岸与近海工程国家重点实验室,辽宁,大连,116024
- 作者简介：
- 基金信息：
- DOI：
  CLC： TU4
- Online First：15 July 2014，
  
  Published：2004
- 稿件说明：
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ZHANG Chuan-qing, YANG Qing, LUAN Mao-tian. An evolutionary neural network model for suction prediction of unsaturated soils[J]. 2004, 25(1).
DOI：

ZHANG Chuan-qing, YANG Qing, LUAN Mao-tian. An evolutionary neural network model for suction prediction of unsaturated soils[J]. 2004, 25(1). DOI：

摘要

利用遗传算法和神经网络，基于不同类型，不同条件下非饱和土的吸力测试数据，建立了一种以含水量为主要因素，耦合密度、初始含水量、先期固结压力、孔隙比5个因素的吸力预测模型。预测结果分析表明，所建的模型能很好地拟合试验结果，从而，验证了该模型的合理性和可行性。

Abstract

By combining genetic algorithm and artificial neural network

an evolutionary neural network model is established for the suction prediction of unsaturated soil. In the model

total density

initial water content

pressure preconsolidated and void ratio are considered. The predicted results

which were obtained through the created model

indicate that this model is well in accord with the test data. It provides a new approach for the research of predicting the shear strength of unsaturated soils.

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Related Institution

School of Highway Engineering, Changsha University of Science & Technology

School of Civil and Architectural Engineering, Central South University

Key laboratory of Rock and Soil Mechanics, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences

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Institute of Geotechnical Engineering, Hohai University

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