| 补偿模糊神经网络在储层参数预测中的应用 |
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| 引用本文： | 甄兆聪,肖慈珣.补偿模糊神经网络在储层参数预测中的应用[J].物探化探计算技术,2002,24(2):124-128. |
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| 作者姓名： | 甄兆聪 肖慈珣 |
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| 作者单位： | 成都理工大学,信息工程学院,成都,610059 |
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| 基金项目： | 国家高技术研究发展计划 ( 86 3计划 )项目 ( 82 0 -0 7-0 2 ) |
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| 摘 要： | 为了克服常规BP神经网络法在预测储层参数中出现学习速度慢、无法结合专家知识等不足，我们引入了补偿模糊神经网络。它是一个结合了补偿模糊逻辑和神经网络的混合系统，由面向控制和面向决策的神经元组成，其模糊运算采用动态的、全局优化运算，学习速度快、学习过程稳定，将其用于储层参数预测效果良好。
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| 关 键 词： | 补偿模糊神经网络 模糊逻辑 神经网络 储层参数预测 ANH |
| 文章编号： | 1001-1749(2002)02-0124-05 |
| 修稿时间： | 2001年12月27 |
APPLICATION OF CFNN IN PREDICTION OF RESERVOIR PARAMETERS |
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| ZHEN Zhao cong,XIAO Ci xun.APPLICATION OF CFNN IN PREDICTION OF RESERVOIR PARAMETERS[J].Computing Techniques For Geophysical and Geochemical Exploration,2002,24(2):124-128. |
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| Authors: | ZHEN Zhao cong XIAO Ci xun |
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| Abstract: | General BP neural networks(BPNN) has several lacks, such as slow learning speed and being not able to combine with the expert knowledge etc. In order to overcome these lacks we introduce the compensative fuzzy neural network(CFNN), which combines compensative fuzzy logic and neural network, and is composed of control oriented cell and decision-making cell. It's fuzzy computation is dynamic and global optimized, therefore its speed is fast. It turns out that CFNN is effective in prediction of reservoir parameters. |
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| Keywords: | CFNN fuzzy logic neural network prediction of reservoir parameters |
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