首页> 外文会议>7th international symposium on test and measurement (ISTM/2007) >Design of Indirectly Measuring Model Based on Fuzzy C-Mean Cluster Neural Network
【24h】

Design of Indirectly Measuring Model Based on Fuzzy C-Mean Cluster Neural Network

机译:基于模糊C均值聚类神经网络的间接测量模型设计

获取原文
获取外文期刊封面目录资料

摘要

Based on simple introduction of Neural Network and Fuzzy Logic, this article discusses a method utilizing Fuzzy C mean cluster and RBF network, and constructs indirect measurement's model in this way. This technique fits non-linear model very well and can improve measurement's accuracy and reliability effectively.
机译:在简单介绍神经网络和模糊逻辑的基础上,本文讨论了一种利用模糊C均值聚类和RBF网络的方法,并以此方式构建了间接测量模型。该技术非常适合非线性模型,可以有效地提高测量的准确性和可靠性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号