首页> 外文会议>International Conference on Measuring Technology and Mechatronics Automation >Hyper-Chaotic Neural Network Based on Newton Iterative Method and Its Application in Solving Load Flow Equations of Power System
【24h】

Hyper-Chaotic Neural Network Based on Newton Iterative Method and Its Application in Solving Load Flow Equations of Power System

机译:基于牛顿迭代方法的超混沌神经网络及其在求解电力系统载荷流动方程中的应用

获取原文

摘要

Most of load flow equations of power system are multi-variable nonlinear equations set which need to know the initial value for solving, and the initial value is very difficult to choose. Neural network is a kind of highly complex nonlinear dynamic system and chaotic phenomenon is found in it. By utilizing the simulated annealing mechanism to eliminate transiently chaotic neuron, this paper presents a kind of chaotic neuron which can permanently sustain chaotic search. The topology of chaotic neural network composed of four chaotic neurons in which hyper-chaos exists is studied. For the first time, a novel method to find all solutions of nonlinear equations is proposed in which initial points are generated by hyper-chaotic neural network. The numerical example shows that the new method proposed in this paper is correct and effective, and it lays a good engineering foundation for finding all the solutions of load flow equations of power system.
机译:电力系统的大多数负载流程方程是多变量非线性方程式设置,需要了解求解的初始值,并且初始值非常难以选择。神经网络是一种高度复杂的非线性动态系统,并在其中发现混乱现象。通过利用模拟的退火机制来消除瞬时混沌神经元,本文呈现了一种混沌神经元,可以永久地维持混沌搜索。研究了由四种混沌神经元组成的混沌神经网络的拓扑,其中存在超混乱。首次,提出了一种寻找所有非线性方程解决方案的新方法,其中由超混沌神经网络产生初始点。该数值示例表明,本文提出的新方法是正确且有效的,并且它为找到电力系统的负载流程方程的所有解决方案而言。

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