| 基于密度聚类补偿模糊神经网络的建模方法 |
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| 引用本文： | 王婷婷. 基于密度聚类补偿模糊神经网络的建模方法[J]. 科学技术与工程, 2010, 10(13) |
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| 作者姓名： | 王婷婷 |
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| 作者单位： | 1. 辽宁石油化工大学信息与控制工程学院,抚顺,113001
2. 渤海钻探第二录井分公司,任丘,062552 |
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| 摘 要： | 补偿模糊神经网络是综合补偿模糊逻辑和神经网络的混合系统。提出了将密度聚类算法运用到补偿模糊神经网络的输入模糊化和规则提取中。通过该方法对非线性系统的建模,仿真结果证明改进后的网络在提取规则、误差精度、收敛速度等方面均优于传统补偿模糊神经网络。
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| 关 键 词： | 补偿模糊神经网络 密度聚类 建模 模规则 |
| 收稿时间： | 2010-01-25 |
| 修稿时间： | 2010-01-25 |
Compensatory Fuzzy Neural Network Modeling Method Based On Density Clustering |
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| wangtingting. Compensatory Fuzzy Neural Network Modeling Method Based On Density Clustering[J]. Science Technology and Engineering, 2010, 10(13) |
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| Authors: | wangtingting |
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| Affiliation: | College of Information and Control Engineering/a>;Liaoning Shihua University/a>;Fushun 113001/a>;P.R.China/a>;No.2 Mud Logging Company/a>;BHDC1/a>;Renqin 062552/a>;P.R.China |
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| Abstract: | Compensatory fuzzy neural network is a hybrid system which integrates compensation fuzzy logic and neural network.A method that applied the density clustering algorithm to the input fuzzy and rules extraction of compensatory fuzzy neural network is presented.Through the modeling of nonlinear system applied the method presented,the simulation result show that the extraction rules,the error precision,convergence rate of improved network are all superior to the traditional. |
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| Keywords: | compensatory fuzzy neural network density Clustering modeling rules of fuzzy |
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