计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (28): 51-53.DOI: 10.3778/j.issn.1002-8331.2010.28.015

• 研究、探讨 • 上一篇    下一篇

改进的区间值模糊集交互式遗传算法

胡晓辉,陈俊莲,张晓颖   

  1. 兰州交通大学 电子与信息工程学院,兰州 730070
  • 收稿日期:2009-03-24 修回日期:2009-05-18 出版日期:2010-10-01 发布日期:2010-10-01
  • 通讯作者: 胡晓辉

Improved interactive genetic algorithm with interval value fuzzy set

HU Xiao-hui,CHEN Jun-lian,ZHANG Xiao-ying   

  1. Institute of Electronic and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China
  • Received:2009-03-24 Revised:2009-05-18 Online:2010-10-01 Published:2010-10-01
  • Contact: HU Xiao-hui

摘要: 区间值模糊集的交互式遗传算法,能有效缓解用户的疲劳,同时避免用户因一时无法给出确定值而浪费掉的时间,大大加快了收敛速度。首先采用区间值模糊集的方法表示对个体进行评价的适应度值,即为区间适应度值,然后对其进行排序,按照排序结果采用交互式遗传算法进行全局搜索。整个过程符合人的思维过程,能有效搜索到用户满意的个体。将该方法应用于图像检索系统中,结果表明该方法有效地提高了检索速度,并且取得了较好的检索结果。

关键词: 交互式遗传算法, 区间值, 区间值模糊集, 区间适应度值

Abstract: Interactive genetic algorithm with interval value fuzzy set can effectively alleviate user fatigue and avoid wasting time while user cannot give a precise value.This can largely quicken convergence velocity.At first,the way of interval value fuzzy set is adopted to indicate the result which is used to evaluate individual fitness value.It is called interval fitness value.Then it is sorted and its result is used to retrieve overall with interactive genetic algorithm.All the retrieval processes are in accordance with human thinking processes and can effectively retrieve satisfied individual.The method is used to image retrieval system and the results demonstrate that the method can effectively improve retrieval velocity and retrieve much better results.

Key words: interactive genetic algorithm, interval value, interval value fuzzy set, interval fitness value

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