| 基于粗糙集理论的RBF神经网络剪枝算法 |
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| 引用本文： | 韩丽,史丽萍,徐治皋.基于粗糙集理论的RBF神经网络剪枝算法[J].信息与控制,2007,36(5):604-609,615. |
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| 作者姓名： | 韩丽 史丽萍 徐治皋 |
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| 作者单位： | 1. 中国矿业大学信息与电气工程学院,江苏,徐州,221000
2. 东南大学能源与环境学院,江苏,南京,210096 |
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| 摘 要： | 分析了满足给定学习误差要求的最小结构神经网络的各种实现方法.把粗糙集理论引入神经网络的结构构造中;提出了一种基于粗糙集理论的RBF神经网络剪枝算法,并将这种算法与现有剪枝算法相比较.最后将该算法应用于热工过程中过热气温动态特性建模.仿真结果表明基于该算法的神经网络模型具有较高的建模精度以及泛化能力.
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| 关 键 词： | 粗糙集 剪枝 |
| 文章编号： | 1002-0411（2007）05-0604-06 |
| 修稿时间： | 2006-07-26 |
A Pruning Algorithm for RBF Neural Network Based on Rough Sets |
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| HAN li,Shi Li-ping,XU Zhi-gao.A Pruning Algorithm for RBF Neural Network Based on Rough Sets[J].Information and Control,2007,36(5):604-609,615. |
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| Authors: | HAN li Shi Li-ping XU Zhi-gao |
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| Affiliation: | 1.School of Information and Electronic Engineering,China University of Mining and Technology,Xuzhou 221000,China;2.School of Energy and Environment,Southeast University,Nanjing 210096,China |
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| Abstract: | Methods to achieve the smallest sized network which can learn the training data within a given error bound are analyzed.Rough sets theory is applied to construct neural networks.A pruning algorithm for RBF(radial basis function) neural network based on rough sets is proposed,and this algorithm is compared with the existing methods.The proposed algorithm is applied to build the dynamic model of the superheated steam temperature in thermal process.Simulation is made,and the results show that the neural model based on this algorithm is of high approximation accuracy and good generalization ability. |
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| Keywords: | RBF |
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