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基于PSO-SVM的空气钻井地下水水位预测
引用本文:肖军民,刘慧升. 基于PSO-SVM的空气钻井地下水水位预测[J]. 价值工程, 2011, 30(21): 48-48
作者姓名:肖军民  刘慧升
作者单位:1. 中国石化江汉油田分公司采气厂,万州,404020
2. 中国石化江汉油田分公司采油厂,万州,404020
摘    要:为缩短兴隆气田空气钻井周期,降低钻井成本,需对地下水水位进行预测。结合粒子群算法(PSO)和支持向量机(SVM),提出了一种新的空气钻井地下水水位预测模型。结果表明,该模型具有收敛快、预测精度高等特点,在空气钻井地下水位预测中具有一定的工程应用价值。

关 键 词:粒子群  支持向量机  空气钻井  水位预测

Forecast of Groudwater Level of Air Drilling Based on PSO-SVM
Xiao Junmin,Liu Huisheng. Forecast of Groudwater Level of Air Drilling Based on PSO-SVM[J]. Value Engineering, 2011, 30(21): 48-48
Authors:Xiao Junmin  Liu Huisheng
Affiliation:①Xiao Junmin;②Liu Huisheng(①Gas Plant of Sinopec Jianghan Oilfield,Wanzhou 404020,China;②Oil Plant of Sinopec Jianghan Oilfield,Wanzhou 404020,China)
Abstract:To reduce the well drilling period and cost in Northeast Sichuan,it needs forecast the groundwater level.Combined with the PSO and SVM,a new forecast model for groundwater level was proposed.The computed result showed that the model had fast astringency and high precision.It would have engineering using value in the groundwater level forecast of air drilling.
Keywords:PSO  SVM  air drilling  groundwater level forecast  
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