青岛大学学报（自然科学版）2017，Vol.30Issue(3)：76-80,5.DOI:10.3969/j.issn.1006-1037.2017.08.16
基于主成分分析和核主成分分析的地震属性优化的研究
Seismic Attribute Optimization Research Based on Principal Component Analysis and Kernel Principal Component Analysis
郑和忠 1魏长江 1王树华2
作者信息
- 1. 青岛大学数据科学与软件工程学院,青岛266071
- 2. 胜利油田勘探开发研究院西部分院,东营257000
- 折叠
摘要
Abstract
In the seismic attribute analysis technique,seismic attribute optinization is an important step.Principal cornponent analysis is a comrnonly used method of seisrnic attribute optimization based on effective linear transformation,but it is not good to reduce the seismic attribute data with nonlinear relationship.A kernel principal component analysis method based on nonlinear transformation is proposed.This method maps the low-dimensional input space to the high-dimensional feature space through the kernel function,realizing the transformation from nonlinear to linear relation of seismic attribute data,and then optimizes the attribute by principal component analysis.The experimental results show that the proposed method has better effect on the seismic attribute optimization of nonlinear relation than principal component analysis.关键词
地震属性优化/主成分分析/降维/核主成分分析Key words
seismic attribute optimization/principal component analysis/dimensionality reduction/kernel principal component analysis分类
信息技术与安全科学引用本文复制引用
郑和忠,魏长江,王树华..基于主成分分析和核主成分分析的地震属性优化的研究[J].青岛大学学报（自然科学版）,2017,30(3):76-80,5.
