| 基于遗传算法的神经网络油水层识别 |
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| 引用本文： | 曾黄麟,李娟. 基于遗传算法的神经网络油水层识别[J]. 四川轻化工学院学报, 2010, 0(5): 590-593 |
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| 作者姓名： | 曾黄麟 李娟 |
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| 作者单位： | [1]四川理工学院自动化与电子信息学院,四川自贡643000 [2]山西工商职业学院计算机系,太原030000 |
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| 基金项目： | 国家高技术研究发展计划（863计划）第四批课题（2008AA11A134） |
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| 摘 要： | 文章研究了基于遗传算法的神经网络油水层识别方法,针对神经计算存在因输入信息空间维数较大而使网络结构复杂、训练时间长,以及因冗余属性使网络拟合精度不高等缺点,提出了基于粗集属性约简方法降低了输入信息的空间维数、减少了运算量和简化了神经网络的拓扑结构,利用遗传算法提高神经网络的训练速度。实验结果表明：将混合智能计算方法应用于油水层识别中效果显著,其学习训练速度和拟合精度远优于传统BP神经网络算法。
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| 关 键 词： | 属性约简 神经网络 遗传算法 油水层识别 |
An Oil-water Layer Recognition Based on a Genetic Algorithm Neural Network |
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| ZENG Huang-lin,LI Juan. An Oil-water Layer Recognition Based on a Genetic Algorithm Neural Network[J]. Journal of Sichuan Institute of Light Industry and Chemical Technology, 2010, 0(5): 590-593 |
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| Authors: | ZENG Huang-lin LI Juan |
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| Affiliation: | 1.School of Automation and Electronic Information,Sichuan University of Science ＆Engineering,Zigong 643000,China;2.Department of Computer Science,Shanxi College of Bussiness and Technology,Shanxi 030000,China) |
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| Abstract: | In this paper,a composition intelligence computing method is suggested for an oil-water layer recognition.The redundant condition attributes are reduced based on rough set attribute simplification algorithm so that an oil-water layer neural network recognition system can be simplified to improve network composition.An optimization computation speed of neural network is improved by a BP learning with a genetic algorithm.Simulation result shows that the effect in oil-water layer recognition is improved by the composition intelligence computing method proposed here. |
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| Keywords: | attribute reduction neural network genetic algorithm oil-water layer recognition |
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