基于PCA的LS-SVM预测模型应用  

Applications of Forecasting Model Based on PCA-LS-SVM

作　　者：胡剑策[1] 

机构地区：[1]温州医学院,温州325035

出　　处：《计算机系统应用》2012年第6期167-169,共3页Computer Systems & Applications

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。Identification and prediction ofoil 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.

关 键 词：主成分 最小二乘支持向量机 预测 油气 

分 类 号：P631.84[天文地球—地质矿产勘探] P618.13[天文地球—地质学]