文献类型：会议论文

英文题名：Soil water characteristic curves based on particle analysis

作者：Tao, Hongliang[1];Chen, Chen[1];Jiang, Ping[2];Tang, Liyan[2]

机构：[1]Taff Planning & Design Inst Yunan Prov, Kunming City, Yunnan Province, Peoples R China;[2]Shaoxing Univ, Shaoxing City, Zhejiang, Peoples R China

会议论文集：13th Global Congress on Manufacturing and Management (GCMM)

会议日期：NOV 28-30, 2016

会议地点：Zhengzhou Univ, Zhengzhou, PEOPLES R CHINA

主办单位：Zhengzhou Univ

语种：英文

外文关键词：Unsaturated soil; Soil water characteristic curve; Neural network algorithm; Soil particle size distribution parameter model; Arya-Paris model

外文摘要：New calculation method for determining Soil water characteristic curves (SWCC) according to soil particle analysis tests based on BP neural network algorithm and Arya-Paris model. BP Neural network algorithm was used to simulate parameter model of soil particle size distribution based on soil particle analysis tests, and used to simulate the function relationship between soil volumetric water content and matrix suction which were calculated based on Arya-Paris model. The function expression of SWCC can be obtained by BP neural network algorithm based on Arya-Paris model. The result show that this method was applicability and reliability. (C) 2017 The Authors. Published by Elsevier Ltd.