摘要
针对传统非线性方程组解法对初始值敏感、收敛性差、精度低等问题,提出了一种用于人工鱼群算法求解非线性方程组的进化算法。该算法求解精度高、收敛速度快。数值仿真结果表明,该算法对求解非线性方程组非常有效,既克服了传统方法对初值敏感和收敛性差,又解决了非线性方程组多解的求解难点等问题,为非线性方程组提供了一种进化求解的方法。
Aiming at the problems of the classical algorithms for solving nonlinear equations, such as high sensitivity to the initial guess of the solution, poor convergence reliability and can＇ t get all solutions, etc. , the Artificial Fish-Swarm Algorithm （AFSA） which was put forward recently to solve nonlinear equations. The solving results are accurate, the computer simulated results show that this technique overcomes the problems such as sensitivity to initial values, poor convergence reliability, and resolves the difficulty in getting all solutions too. It makes a new method for resolving the nonlinear equations.
出处
《计算机应用研究》
CSCD
北大核心
2007年第6期242-244,共3页
Application Research of Computers
基金
国家自然科学基金资助项目(60461001)
广西自然科学基金资助项目(054204)
广西民族大学重大科研资助项目
关键词
非线性方程组
人工鱼群算法
近似解
进化计算
system of nonlinear equations
artificial fish-swarm algorithm
approximation solution
evolutionary computation
