A novel rough neural network and its training algorithm

被引：0
|
作者：
Sun, Sheng-He [1 ]
Mei, Xiao-Dan [1 ]
Zhang, Zhao-Li [1 ]
机构：
[1] Dept. of Automatic Test and Ctrl., Harbin Institute of Technology, Harbin 150001, China
来源：
IEICE Transactions on Information and Systems | 2002年 / E85-D卷 / 02期
关键词：
Approximation theory - Backpropagation - Data reduction - Genetic algorithms - Iterative methods - Normal distribution - Transfer functions - Two dimensional;
D O I：
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学科分类号：
摘要：
A novel rough neural network (RNN) structure and its application are proposed in this paper. We principally introduce its architecture and training algorithms: the genetic training algorithm (GA) and the tabu search training algorithm (TSA). We first compare RNN with the conventional NN trained by the BP algorithm in two-dimensional data classification. Then we compare RNN with NN by the same training algorithm (TSA) in functional approximation. Experiment results show that the proposed RNN is more effective than NN, not only in computation time but also in performance.
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页码：426 / 431
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