| 基于势函数聚类的改进RBF网络算法研究 |
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| 引用本文： | 黄朝辉,闻辉,车艳.基于势函数聚类的改进RBF网络算法研究[J].延边大学理工学报,2020,0(2):145-149. |
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| 作者姓名： | 黄朝辉 闻辉 车艳 |
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| 作者单位： | ( 莆田学院 信息工程学院, 福建 莆田 351100 ) |
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| 摘 要： | 为优化径向基函数(RBF)网络结构并改善网络泛化性能,提出了一种基于势函数聚类的改进RBF网络算法.首先使用势函数统计每个模式类别中的样本势值,以此实现样本空间中不同样本的势值度量; 其次以增量学习的方式逐次完成对样本空间的有效覆盖,以此实现网络隐节点个数及参数的自动有效估计.最后将本文算法与KMRBF、FCRBF、MRAN以及 GAP -RBF 学习算法进行了实验对比,结果表明本文算法的网络分类精度更高,克服了KMRBF和FCRBF算法需人工调整网络隐节点来提高分类精度的问题,且比 GAP -RBF和MRAN算法的网络结构更加简单.
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| 关 键 词： | 径向基函数 增量学习 势函数 神经网络 |
Research on improved RBF network algorithm based on potential function clustering |
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| HUANG Chaohui,WEN Hui,CHE Yan.Research on improved RBF network algorithm based on potential function clustering[J].Journal of Yanbian University (Natural Science),2020,0(2):145-149. |
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| Authors: | HUANG Chaohui WEN Hui CHE Yan |
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| Affiliation: | ( Department of Information Engineering, Putian University, Putian 351100, China ) |
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| Abstract: | To optimize the structure of radial basis function(RBF)network and improve its generalization performance, an improved RBF network based on potential function clustering is proposed. Firstly, the potential function is used to count the potential values of samples in each pattern category, so as to measure the potential values of different samples in the sample space. Secondly, the incremental learning method is used to cover the sample space step by step, so as to complete the automatic and effective estimation of the number of hidden nodes and parameters in the network. Finally, the presented algorithm is compared with KMRBF, FCRBF, MRAN and GAP -RBF learning algorithm by experiments. The results and experiments show that the classification accuracy of thealgorithm is higher than that of KMRBF, FCRBF, GAP -RBF and MRAN, which overcomes the problem that KMRBF and FCRBF algorithm need many experiments to adjust the hidden nodes manually to obtain higher classification accuracy, and is more simple than the GAP -RBF and MRAN network structure. |
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| Keywords: | radial basis function incremental learning potential function neural network |
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