摘要
基于在求解非线性方程组过程中传统算法存在着对于初始点敏感和串行运行速度过慢的问题,提出一种求解非线性方程组的进化策略算法。该算法充分发挥了进化策略的群体搜索和全局收敛的特性,能够快速求得非线性方程组的根,有效地克服了经典算法的初始点敏感和速度过慢的问题。仿真计算表明,该算法比传统的经典算法、改进的遗传算法和神经网络算法具有更高的求解质量和求解效率,为求解非线性方程组提供了一条比较有效的途径。
Evolution strategies algorithm to solve nonlinear equation groups is presented, according to the question that traditional algorithm has sensitivity to initial point and too slow velocity by serial operation. The algorithm sufficiently exerted the advantage of ES such as group search and global convergence, which can quickly find the roots of the nonlinear equations. It can efficiently overcome the problem of high sensitivity to initial point and too slow velocity. Results of the simulation indicated the evolution strategies algorithm had better efficiency and optimization performance than traditional classical algorithms, improved genetic algorithm and neural network algorithm, which offers an effective way to solve the nonlinear equations from another viewpoint.
出处
《计算机工程与设计》
CSCD
北大核心
2009年第11期2634-2636,共3页
Computer Engineering and Design
关键词
非线性方程组
进化策略
全局收敛
突变
标准差
nonlinear equations
evolution strategies
global convergence
mutation
standard deviation
