控制理论与应用2011，Vol.28Issue(5)：610-618,9.
基于半监督学习的变种群规模区间适应值交互式遗传算法
Interval-fitness interactive genetic algorithms with varying population size based on semi-supervised learning
摘要
Abstract
In order to alleviate user fatigue and improve the performances of interactive genetic algorithms (IGAs) in exploration, we present the interval-fitness interactive genetic algorithms with varying population size based on a co-training semi-supervised learning(CSSL). According to the clustering results of a large population, we develop the strategy for selecting unlabeled samples and labeled samples. Based on the approximation precision of two co-training learners, an efficient strategy for selecting high reliable unlabeled samples for labeling is given. Then, the CSSL mechanism is employed to train two radial basis function(RBF) neural networks in order to establish the surrogate model with high precision and good generalization ability. In the subsequent evolution, the surrogate model is used to estimate the fitness of an individual; in turn, the surrogate model is updated based on its estimation error. The proposed algorithm is analyzed and applied to a fashion evolutionary design system. The experimental results show its efficacy.关键词
交互式遗传算法/区间适应值/半监督学习/代理模型/变种群规模Key words
interactive genetic algorithms/ interval fitness/ semi-supervised learning/ surrogate model/ varying population size分类
信息技术与安全科学引用本文复制引用
孙晓燕,任洁,巩敦卫..基于半监督学习的变种群规模区间适应值交互式遗传算法[J].控制理论与应用,2011,28(5):610-618,9.基金项目
国家自然科学基金资助项目(60775044) （60775044）
教育部新世纪优秀人才支持计划资助项目(NCET-07-0802) （NCET-07-0802）
江苏省自然科学基金资助项目(Bk2010186) （Bk2010186）
江苏省博士后基金资助项目(1001019C). （1001019C）
