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Received:December 06, 2011 Revised:February 17, 2012
Received:December 06, 2011 Revised:February 17, 2012
中文摘要: 油气储层的识别和预测是当今热门的研究课题。本文以实地测井数据为基础,提出基于PCA 的LS-SVM预测模型对储层油气进行分类预测,并与人工神经网络预测模型对比。结果表明,该模型的性能优于其它模型,具有一定的应用价值。
Abstract:Identification and prediction of oil and gas reservoirs are popular research topic today. Based on logging data, the proposed PCA-based LS-SVM forecasting model is applied identify oil and gas reservoirs, comparing with artificial neural network prediction model. The results show that the model's performance is stronger than other models, has a certain value.
文章编号： 中图分类号： 文献标志码：
基金项目:
| Author Name | Affiliation |
| HU Jian-Ce | Wenzhou Medical College,Wenzhou 325035, China |
| Author Name | Affiliation |
| HU Jian-Ce | Wenzhou Medical College,Wenzhou 325035, China |
引用文本：
胡剑策.基于PCA 的LS-SVM 预测模型应用.计算机系统应用,2012,21(6):167-169
HU Jian-Ce.Applications of Forecasting Model Based on PCA-LS-SVM.COMPUTER SYSTEMS APPLICATIONS,2012,21(6):167-169
胡剑策.基于PCA 的LS-SVM 预测模型应用.计算机系统应用,2012,21(6):167-169
HU Jian-Ce.Applications of Forecasting Model Based on PCA-LS-SVM.COMPUTER SYSTEMS APPLICATIONS,2012,21(6):167-169
