期刊文献+

基于人工神经网络的崩岸预测模型研究 被引量:3

Artificial neural network-based bank collapse prediction model
下载PDF
导出
摘要 针对崩岸影响因素众多、难以定量评价等问题,采用一种基于人工神经网络的崩岸预测方法,介绍了其基本原理.在研究崩岸诸多影响因素的基础上,选取11种主要影响因素建立崩岸预测模型.以随机构造的20个岸坡模型为训练样本,以5个随机岸坡模型为检验样本,实现了岸坡稳定性的人工神经网络预测.初步结果表明,神经网络方法可以应用于崩岸的预测. In consideration of many influencing factors and some difficulties in quantitative evaluation, the artificial neural network (ANN)-based bank collapse prediction method was adopted, and its principle was introduced. By selection of 11 main influencing factors, a bank collapse prediction model was established. Then 20 bank-slope models, which were randomly generated, were taken as training samples, and 5 random bank-slope models as testing samples, the bank-slope stability was predicted by use of the present model. The result shows that the ANN method can be used for bank collapse prediction.
出处 《河海大学学报(自然科学版)》 CAS CSCD 北大核心 2007年第5期514-517,共4页 Journal of Hohai University(Natural Sciences)
基金 江苏重点水利科技资助项目(2001048) 国家重点基础研究发展计划(973计划)资助项目(2007CB714102)
关键词 崩岸 预测 人工神经网络 bank collapse prediction artificial neural network (ANN)
  • 引文网络
  • 相关文献

参考文献8

二级参考文献37

共引文献378

同被引文献31

引证文献3

二级引证文献24

;
使用帮助 返回顶部