Neural networks method for computation of autocovariance distance

SHE Yue-xin; LIU Han-long; GAO Yu-feng

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Neural networks method for computation of autocovariance distance

更新时间：2026-06-25

- Neural networks method for computation of autocovariance distance
- Vol. 24, Issue 5, (2003)
- 作者机构：
  
  1. 淮阴工学院建筑工程系,江苏,淮安,223001
  2. 河海大学岩土工程研究所,江苏,南京,210098
- 作者简介：
- 基金信息：
- DOI：
  CLC： TU412
- Online First：19 August 2014，
  
  Published：2003
- 稿件说明：
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SHE Yue-xin, LIU Han-long, GAO Yu-feng. Neural networks method for computation of autocovariance distance[J]. 2003, 24(5).
DOI：

SHE Yue-xin, LIU Han-long, GAO Yu-feng. Neural networks method for computation of autocovariance distance[J]. 2003, 24(5). DOI：

摘要

通过对GRNN网络分析

导出了网络参数spread与平方指数相关函数参数r0之间的关系

提出了基于GRNN的计算相关距离和拟合相关曲线的方法。研究表明，在最优spread参数条件下GRNN网络能够较为准确地映射实测土性曲线的变化特征，反映土性空间的相关特征。

Abstract

General regression neural networks(GRNN) are briefly analyzed. The relationship between the parameter spread of GRNN and the parameter r0 of autocovariance function (squared exponential function) is derived

and the method for computation of autocovariance distance and fitting of autocovariance function is presented based on GRNN. The study indicates that with optimum spread

GRNN can reflect the variability of soil property and the characteristics of spatial autocovariance.

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