埕北海域表层沉积物抗剪强度BP神经网络模拟分析  

Prediction of Shear Strength Parameters of Surface Sediment in Chengbei Sea Area by BP Neural Networks

作　　者：田动会 滕珊 孟磊 刘园园 Tian Donghui;Teng Shan;Meng Lei;Liu Yuanyuan(Experimental Testing Team of Jiangxi Geological Bureau,Nanchang,China)

机构地区：[1]江西省地质局实验测试大队,江西南昌

出　　处：《科学技术创新》2023年第3期92-95,共4页Scientific and Technological Innovation

基　　金：江西省地质局科技创新项目“江西省伴生放射性矿山土壤污染防治技术研究”(编号:20204BCJ22019)科研成果。

摘　　要：运用BP神经网络对埕北海域213个海底表层沉积物抗剪强度与物理性质的关系模拟分析神经网络映射关系,并引入相对作用强度分析,获取影响抗剪强度的主要因素和次要因素,作为评估和预测土体抗剪强度的经验指标,对海岸工程地质评价、施工维护有一定的借鉴价值。Based on the analysis of 181 grain size testing data which sampled in Chengbei sea area, and the application of BP neural networks in the study area, the result show that the sediment is mainly composed of sand,silty sand, sandy silt, silt and clayey silt. The paper research the effect of physical property parameters to shear strength and make the BP neural networks model to predict the shear strength parameters of surface sediment in the study area. And with the relative strength of effect, the different roles of relevant factors are analysed according to the data, the result has proved the efficiency of relative strength of effect.And that is a powerful tool for the factor analysis of the shear strength of surface sediment.

关 键 词：埕北海域 表层沉积物 BP神经网络 物理性质指标 抗剪强度 

分 类 号：P736.2[天文地球—海洋地质]