中文摘要：

自然科学与工程中的许多问题都可以转化为非线性方程组的求解问题。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。机构综合与近似综合实例表明，该算法对求解非线性方程组非常有效，求解精度高、收敛速度快，解决了非线性方程组的初值敏感和多解的求解难点等问题，为机构综合与近似综合提供了一种进化求解的方法。

英文摘要：

Many questions in natural science and engineering can be transformed into nonlinear equations and solved. Aimed 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） was put forward to solve nonlinear equations. The numerical examples in linkage synthesis and approximate synthesis show that this algorithm has the characteristic of high precision and fast convergence speed, and resolves the difficulty in getting all solutions.