一种改进的遗传算法分析

Analysis of an improved genetic algorithm

遗传算法是复杂的非线性科学和人工智能科学的前沿,遗传算法具有不受搜索空间限制性假设的约束,也不受模型参数数目与约束条件的束缚等特点,它的优点在于全局寻优。文章通过算法改进,找到最优个体,加快收敛速度,克服过早收敛的缺点。

Genetic algorithm is a complex nonlinear science and artificial intelligence science frontier, the genetic algorithm has characteristic of not restrained by the search space restriction hypothesis and not restrained by number and constraint conditions of model parameters, it has the advantages of global optimization. The article finds the optimal individual, speeding up the convergence rate and overcoming the premature convergence through algorithm improvement.