长春师范大学学报2024,Vol.43Issue(10) :17-22.

基于梯度加权重构的一类五阶收敛改进牛顿迭代法

A Class of Improved Newton Iterative Methods with Fifth-Order Convergence Based on Gradient Weighted Reconstruction

郭巧 杨兵 吴昌广
长春师范大学学报2024,Vol.43Issue(10) :17-22.

基于梯度加权重构的一类五阶收敛改进牛顿迭代法

A Class of Improved Newton Iterative Methods with Fifth-Order Convergence Based on Gradient Weighted Reconstruction

郭巧 1杨兵 2吴昌广3
扫码查看

作者信息

  • 1. 安徽职业技术学院计算机与信息技术学院,安徽 合肥 230611
  • 2. 安徽职业技术学院智能智造学院,安徽 合肥 230611
  • 3. 南京理工大学计算机学院,江苏南京 210094
  • 折叠

摘要

经典牛顿迭代法是一种求解非线性方程在实数域及复数域上近似值的方法,可通过变上线积分函数推导实现.利用曲边梯形面积近似化得到四个变上线积分函数,通过梯度加权重构赋值得到一类五阶收敛的求解非线性方程近似根的改进牛顿迭代法,收敛性分析和数值实例验证该方法收敛速度较快,并且能够有效避免重根附近发散.该方法在非线性工程领域、经济领域和人工智能领域具有非常广泛的应用.

Abstract

The classical Newton iterative method is a way for solving nonlinear equations in the real and complex domains by approxima-ting the roots of nonlinear equations,which can be realized by deriving the integration functions on variable lines.The four integral func-tions are obtained by approximating the area of curved-edge trapezoid,and the improved Newton's iterative method for solving the ap-proximate roots of nonlinear equations with fifth-order convergence is obtained by the gradient-weighted reconstruction assignment.The convergence analysis and numerical examples verify that this method has a fast convergence rate and can effectively avoid divergence near multiple roots.It has a very wide range of applications in the field of nonlinear engineering,economics and artificial intelligence.

关键词

加权/五阶收敛/非线性方程/改进牛顿迭代

Key words

weighted/fifth-order convergence/nonlinear equationin/improved Newton iteration

引用本文复制引用

出版年

2024
长春师范大学学报
长春师范学院

长春师范大学学报

CHSSCD
影响因子:0.312
ISSN:1008-178X
段落导航相关论文