摘要
通过对模糊神经网络和训练样本的构造,训练模糊神经网络使其达到一定的精度要求后,对网络进行裁剪.在网络隐层的激活和聚类后,提取规则的步骤,从而实现在数据库中获取有效知识的目的,并在应用中进行了仿真,验证了算法的有效性.
By means of constructing fuzzy neural network and training specimen and training the fuzzy neural network to meet the requirement of a certain accuracy, the network was pruned. After the activation and clustering of the hidden layers in the network, the rule sequence was extracted so that the goal of getting effective knowledge from data-base could be realized. The algorithm presented was simulated during its application and proved to be effective.
出处
《兰州理工大学学报》
CAS
北大核心
2007年第3期112-115,共4页
Journal of Lanzhou University of Technology
基金
甘肃省科技攻关项目(2GS044-AS2-011-28)
关键词
模糊神经网络
数据挖掘
规则提取
裁剪
聚类
fuzzy neural network
data mining
rule extraction
pruning
clustering
