摘要
叙述了解非线性方程的一种自适应变搜索区间的遗传算法(GANE)。数值实验表明该算法大大增强了一般遗传算法的性能;在求解非线性方程(组)时,克服了传统方法的某些局限性,完全不需要考虑初始值的选取以及初始区间的确定,甚至在有多个根的任意区间内也可以高效地搜索到精度较高的各个根。
In this paper,an improved genetic algorithm used in solving the nonlinear equation is proposed.In this improved genetic algorithm,the most crucial parameters and the search interval are presented to cope with problems.Our experiments show that this improved genetic algorithm is practical and efficient compared with the normal genetic algorithm.In solving the nonlinear equation,it doesn't take the initial value and the initial interval into consideration and even though in one interval that has not only one root,it also can efficiently figure out every roots,so it conquer the traditional method's limitation.
出处
《计算机工程与应用》
CSCD
北大核心
2005年第21期58-60,共3页
Computer Engineering and Applications
基金
国家自然科学基金项目(编号:100010308)资助
关键词
遗传算法
适应度
变异概率
杂交概率
搜索区间
非线性方程(组)
Genetic Algorithm,fitness value,probability of mutation,probability of crossover,search interval,nonlinear equation