基于模糊邻域差分进化算法求解非线性方程组  

Solving Nonlinear Equation Systems via Fuzzy Neighborhood Differential Evolution Algorithm

作　　者：陈馨 韦慧 CHEN Xin;WEI Hui(School of Mathematics and Big Data,Anhui University of Science and Technology,Huainan 232001,China)

机构地区：[1]安徽理工大学数学与大数据学院,安徽淮南232001

出　　处：《牡丹江师范学院学报（自然科学版）》2023年第1期1-4,共4页Journal of Mudanjiang Normal University：Natural Sciences Edition

基　　金：安徽省自然科学基金项目(2108085MA14);安徽省博士后基金项目(2019B318)。

摘　　要：讨论模糊邻域概率函数选择策略对算法寻根率和成功率的影响.实验结果表明,凸函数类型的概率选择函数较适用于求解多根和搜索空间较广问题,定值概率选择函数较适合于求解含有大量线性方程的问题.选用适当概率选择函数可以提高模糊邻域差分进化算法寻根率和成功率.The influence of fuzzy neighborhood probability selection strategies on algorithm root ratio and success rate is discussed.The experimental results show that convex functions are suitable for solving problems with multiple roots and wide search space problems,fixed-value probability selection functions are suitable for solving problems containing large number of linear equations.Choosing an appropriate probability selection function can improve the root ratio and success rate of the fuzzy neighborhood-based differential evolution with orientation algorithm(FNODE).

关 键 词：差分进化算法 非线性方程组 模糊邻域 概率选择函数 

分 类 号：O241.7[理学—计算数学]