Fuzzy Chance-Constrained Goal Programming Model and Algorithm of Oilfield Measures

被引：0

作者：

Song, Jiekun ^{[1
]}

Song, Jiepeng ^{[2
]}

Zhang, Yu ^{[3
]}

Zhang, Zaixu ^{[1
]}

Fan, Shuiqing ^{[1
]}

机构：

[1] China Univ Petr E China, Coll Econ & Management, Dongying 257061, Peoples R China

[2] Xyzhou Normal Univ, Kewen Inst, Xuzhou 221116, Peoples R China

[3] Financial Assests Ctr Dongxin Unit, Shengli Oilfield, Dongying 257091, Peoples R China

来源：

ADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 2, PROCEEDINGS | 2009年 / 5552卷

关键词：

Oilfield measures; fuzzy chance-constrained goal programming model; hybrid intelligent algorithm; sensitivity analysis;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Measures programming is an important way for improving the effect of measures of oil fields. Based on the theory of fuzzy chance-constrained goal programming, a fuzzy chance-constrained goal programming model is put forward for Measures programming of Oilfield, which uses the increasing, production and cost as objectives. The process of its hybrid intelligent algorithm including fuzzy simulation, genetic algorithm and neural network is provided. and the sensitivity analysis on uncertain factors to determine the influence oil the optimal result can also be carried oil. Finally, an example is given to illustrate the validity of the model and approach.

引用

页码：43 / +

页数：2

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