摘要
针对交互式遗传算法中人的疲劳问题,提出一种基于神经网络(NN)的个体适应度分阶段估计方法,给出了神经网络估计进化个体适应度与人的评价之间的转换策略以及神经网络学习效果的评价指标,并分析了算法的复杂性.实例结果验证了该方法的有效性.
To the problem of human fatigue in interactive genetic algorithm, a neural network based phase estimation of individual fitness is proposed. Turning strategy between neural network estimate based individual fitness and human evaluation based individual fitness is given. The performance index on learning effect of neural network is also presented. The complexity of the algorithm is analyzed. The instance results show its validity.
出处
《控制与决策》
EI
CSCD
北大核心
2005年第2期234-236,240,共4页
Control and Decision
基金
国家自然科学基金项目(60304016).
关键词
交互式遗传算法
神经网络
适应度
Convergence of numerical methods
Learning algorithms
Neural networks
