| 沉降监测多项式回归分析与神经网络预测 |
| |
| 引用本文： | 田丰,文鸿雁,张静.沉降监测多项式回归分析与神经网络预测[J].海洋测绘,2007,27(4):23-27. |
| |
| 作者姓名： | 田丰 文鸿雁 张静 |
| |
| 作者单位： | 桂林工学院,土木工程系,广西,桂林,541004 |
| |
| 基金项目： | 国家自然科学基金项目(40574002)，广西区自然科学基金项目(0339072) |
| |
| 摘 要： | 使用多项式和切比雪夫(Tchebyshev)多项式分别对沉降监测数据进行回归分析以预测未来沉降值,其中切比雪夫多项式的外推效果较好;应用前向BP神经网络对两种不同的单因子输入模式进行非线性函数逼近,并进行了不同采样步长的比较,实例表明将时间点作为网络的输入对沉降进行预测效果较好。
|
| 关 键 词： | 沉降监测 多项式回归 切比雪夫多项式 神经网络预测 |
| 文章编号： | 1671-3044（2007）04-0023-05 |
| 修稿时间： | 2007-01-15 |
Polynomial Regressive Analysis and Neural Networks Prediction of Subsidence Monitoring |
| |
| TIAN Feng,WEN Hong-yan,ZHANG Jing.Polynomial Regressive Analysis and Neural Networks Prediction of Subsidence Monitoring[J].Hydrographic Surveying and Charting,2007,27(4):23-27. |
| |
| Authors: | TIAN Feng WEN Hong-yan ZHANG Jing |
| |
| Institution: | Department of Civil Engineering, Guilin University of Technology, Guilin, Guangxi, 541004 |
| |
| Abstract: | In order to predict future subsidence value,by employing polynomial and Tchebyshev polynomial expression to carry out regressive analysis towards subsidence monitoring data,the Tchebyshev polynomial can obtain preferable extrapolated result.Applying feed-forward back-propagation network to carry out approximation of nonlinear function towards two different single factorial input mode,and proceeding comparison of different sampling step,experiments prove that taking point in time as network input can obtain preferable result. |
| |
| Keywords: | subsidence monitoring polynomial regressivion tchebyshev polynomial expression neural network prediction |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《海洋测绘》浏览原始摘要信息 |
| 点击此处可从《海洋测绘》下载免费的PDF全文 |
|
