...
首页> 外文期刊>Knowledge-Based Systems >A new type of recurrent fuzzy neural network for modeling dynamic systems
【24h】

A new type of recurrent fuzzy neural network for modeling dynamic systems

机译:一种用于动态系统建模的新型递归模糊神经网络

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

In this paper, a new type of neural network called recurrent fuzzy neural network(RFNN) is proposed to model the fuzzy dynamical systems(FDS). FDS is considered as an order system. The network developed in this paper is based on recurrent neural network (RNN) to capture the dynamical properties of FDS. The training algorithm is derived based on the tool of order derivative. An example is given to demonstrate the validity of the approach.
机译:本文提出了一种新型的神经网络,称为递归模糊神经网络(RFNN),对模糊动力系统(FDS)进行建模。 FDS被视为订单系统。本文开发的网络基于递归神经网络(RNN)来捕获FDS的动力学特性。训练算法是基于阶数导数工具导出的。举例说明了该方法的有效性。

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