%0 Journal Article
%T Application of genetic algorithms in fuzzy design<br>遗传算法在模糊设计中的应用
%A TAN Jian-hao
%A ZHANG Jing
%A <br>谭建豪
%A 章兢
%J 控制理论与应用
%D 2010
%I 
%X A practical scheme of fuzzy design in CAD systems is developed, of which the environment is the currently collected data; the learning unit is the fuzzy optimization algorithm based on the genetic algorithms; the knowledge base is composed of design criteria; the executive part is the design unit. The fuzzy optimization learning algorithm of the regression equation is developed, and the corresponding flow chart is built. Then, the design criterion of a flash size is obtained by using this system; and the stability of the algorithm is verified through some examples. To evaluate the performances of the algorithm, we compare it with the least-squares method(LSM) and the immune-genetic algorithm(IGA); the result shows that our algorithm is faster, with higher precision and stability than the other algorithms.
%K fuzzy design
%K genetic algorithm
%K fuzzy optimization
%K regression equation
%K flash size<br>模糊设计
%K 遗传算法
%K 模糊优化
%K 回归方程
%K 飞边尺寸
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=BF13F5773063503C8CDE4640879F1A58&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=E158A972A605785F&sid=3054A11AD1D7E34A&eid=9B1D77939DDB4B89&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=10