%0 Journal Article
%T Extracting classification rules based on multi artificialfish swarm cooperation algorithm<br>基于多群协同人工鱼群算法的分类规则提取算法
%A DAI Shang-ping
%A JI Ying-li
%A WANG Hu
%A JIN Peng
%A <br>戴上平
%A 姬盈利
%A 王华
%A 金鹏
%J 计算机应用研究
%D 2012
%I 
%X This paper proposed the multi artificial fish swarm cooperation algorithm (MAFWA) based on the work principle of basic artificial fish swarm to extract the classification rules of continuous variable space. It defined a function to evaluate the rules based on the support and confidence, designed the code of artificial fish, defined the formula to calculate some key parameters for its application in extracting classification rules and provided with the detailed step of algorithm. And then it made use of programming in the VC++ 6.0 . Finally, it made an experiment on Iris and Wine data sets to test the algorithm, further more it compared the algorithm of MAFWA with the single artificial fish swarm and multi particle swarm algorithm by using the same data sets of Iris and Wine. The experimental result shows that this algorithm can extract the classification rules with high precision quickly. So the algorithm of MAFWA is available and efficient to resolve the problems related to extracting classification rules of continuous variable.
%K multi artificial fish swarm algorithm
%K classification rule
%K cooperation
%K single artificial fish swarm algorithm
%K multi particle swarm algorithm<br>多群体人工鱼群
%K 分类规则
%K 协同
%K 单群体人工鱼群算法
%K 多种群微粒群算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=F886A295C1E57CC51B9C01A44F21FBEC&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=94C357A881DFC066&sid=937C5AD88B71B15A&eid=0C0A5470C59ABA43&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=17