- 1、本文档共9页,可阅读全部内容。
- 2、有哪些信誉好的足球投注网站(book118)网站文档一经付费(服务费),不意味着购买了该文档的版权,仅供个人/单位学习、研究之用,不得用于商业用途,未经授权,严禁复制、发行、汇编、翻译或者网络传播等,侵权必究。
- 3、本站所有内容均由合作方或网友上传,本站不对文档的完整性、权威性及其观点立场正确性做任何保证或承诺!文档内容仅供研究参考,付费前请自行鉴别。如您付费,意味着您自己接受本站规则且自行承担风险,本站不退款、不进行额外附加服务;查看《如何避免下载的几个坑》。如果您已付费下载过本站文档,您可以点击 这里二次下载。
- 4、如文档侵犯商业秘密、侵犯著作权、侵犯人身权等,请点击“版权申诉”(推荐),也可以打举报电话:400-050-0827(电话支持时间:9:00-18:30)。
- 5、该文档为VIP文档,如果想要下载,成为VIP会员后,下载免费。
- 6、成为VIP后,下载本文档将扣除1次下载权益。下载后,不支持退款、换文档。如有疑问请联系我们。
- 7、成为VIP后,您将拥有八大权益,权益包括:VIP文档下载权益、阅读免打扰、文档格式转换、高级专利检索、专属身份标志、高级客服、多端互通、版权登记。
- 8、VIP文档为合作方或网友上传,每下载1次, 网站将根据用户上传文档的质量评分、类型等,对文档贡献者给予高额补贴、流量扶持。如果你也想贡献VIP文档。上传文档
查看更多
孙晓燕2011} 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.pdf
28 5 Vol. 28 No. 5
2011 5 Control Theory Applications May 2011
: 1000°8152(2011)05°0610°09
, ,
(, 221116)
: ,
, . ,
; ,
; (RBF), ;
, , .
.
: ; ; ; ;
: TP273 : A
Interval-fitness interactive genetic algorithms with
varying population size based on semi-supervised learning
SUN Xiao-yan, REN Jie, GONG Dun-wei
(School of Information and Electrical Engineering, China University of Mining Technology,
Xuzhou Jiangsu 221116, China)
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.
Key words: interactive genetic algorithms; interval fitness; semi-supervised learning; surrogate model; varying popula-
tion size
1 (
文档评论(0)