基于进化规划的变异函数研究

Peihong Fu
{"title":"基于进化规划的变异函数研究","authors":"Peihong Fu","doi":"10.1109/ISA.2011.5873332","DOIUrl":null,"url":null,"abstract":"The question which how to select the most superior fitting mode of variogram is one of basic questions which in current geostatistics not yet completely solves. In view of this question, this article proposed take lag as the weight coefficient to establish objective function and establish the variogram fitting method based on the evolutionary programming. This method dynamic estimates the parameter value, has avoided interdependence of each parameter in the estimate process. It is easily, general, estimated the precision is high, has the widespread application value.","PeriodicalId":128163,"journal":{"name":"2011 3rd International Workshop on Intelligent Systems and Applications","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Research on the Variogram Based on Evolutionary Programming\",\"authors\":\"Peihong Fu\",\"doi\":\"10.1109/ISA.2011.5873332\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The question which how to select the most superior fitting mode of variogram is one of basic questions which in current geostatistics not yet completely solves. In view of this question, this article proposed take lag as the weight coefficient to establish objective function and establish the variogram fitting method based on the evolutionary programming. This method dynamic estimates the parameter value, has avoided interdependence of each parameter in the estimate process. It is easily, general, estimated the precision is high, has the widespread application value.\",\"PeriodicalId\":128163,\"journal\":{\"name\":\"2011 3rd International Workshop on Intelligent Systems and Applications\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 3rd International Workshop on Intelligent Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISA.2011.5873332\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 3rd International Workshop on Intelligent Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISA.2011.5873332","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

如何选择最优的变异函数拟合模式是当前地质统计学尚未完全解决的基本问题之一。针对这一问题,本文提出以滞后为权重系数建立目标函数,建立基于进化规划的变异函数拟合方法。该方法对参数值进行动态估计,避免了估计过程中各参数的相互依赖。它简便、通用、估计精度高,具有广泛的应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Research on the Variogram Based on Evolutionary Programming
The question which how to select the most superior fitting mode of variogram is one of basic questions which in current geostatistics not yet completely solves. In view of this question, this article proposed take lag as the weight coefficient to establish objective function and establish the variogram fitting method based on the evolutionary programming. This method dynamic estimates the parameter value, has avoided interdependence of each parameter in the estimate process. It is easily, general, estimated the precision is high, has the widespread application value.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信