| 基于PCA 的LS-SVM 预测模型应用 |
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| 引用本文： | 胡剑策.基于PCA 的LS-SVM 预测模型应用[J].计算机系统应用,2012,21(6):167-169. |
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| 作者姓名： | 胡剑策 |
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| 作者单位： | 温州医学院,温州,325035 |
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| 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。
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| 关 键 词： | 主成分 最小二乘支持向量机 预测 油气 |
| 收稿时间： | 2011/12/6 0:00:00 |
| 修稿时间： | 2012/2/17 0:00:00 |
Applications of Forecasting Model Based on PCA-LS-SVM |
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| HU Jian-Ce.Applications of Forecasting Model Based on PCA-LS-SVM[J].Computer Systems& Applications,2012,21(6):167-169. |
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| Authors: | HU Jian-Ce |
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| Affiliation: | HU Jian-Ce (Wenzhou Medical College ,Wenzhou 325035, China) |
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| Abstract: | 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. |
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| Keywords: | principal component least squares support vector machine forecasts oil and gas |
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