智能系统学报Issue(1)：98-103,6.DOI:10.3969/j.issn.1673-4785.201304019
基于支持向量机和有序聚类的岩层识别
Stratum identification based on the SVM and ordered cluster
摘要
Abstract
The support vector machine ( SVM ) needs training samples to train itself before identifying stratum , while there are no training samples with stratum identification .Focusing on this problem , this paper puts forward a vector machine classifier based on the ordered clustering algorithm .Firstly, the ordered clustering algorithm is used to get preliminary layered logging data which have been filtered and normalized .Secondly , the training samples are obtained according to preliminary layered outcomes .Finally, the data are layered again by the trained SVM classifi-er.The algorithm is used to automatically identify the lithology of the selected three wells , and compared with the results of the other algorithms .The results of the simulation experiment show that the algorithm overcomes the draw-backs that the labeled data has to adopt when training SVM , and improves the accuracy of each stratum , reaching 85%on average .关键词
岩层识别/支持向量机/有序聚类/训练样本/分类器Key words
stratum identification/support vector machine/ordered clustering/training samples/classifier分类
信息技术与安全科学引用本文复制引用
张多,韩逢庆..基于支持向量机和有序聚类的岩层识别[J].智能系统学报,2014,(1):98-103,6.基金项目
国家自然科学基金资助项目（51208538）． （）
