%0 Journal Article
%T Study of Fault Diagnosis Based on New Rough Set-Neural Networks<br>基于一种新型粗糙集神经网络的故障诊断*
%A ZHANG Xi-bin
%A CHENG Li
%A YU Jiang-min
%A <br>张喜斌
%A 成立
%A 余江民
%J 计算机应用研究
%D 2006
%I 
%X A new rough set-neural network based on Self Organized Feature Map(SOFM) network is presented in this paper.Rough set theory has powerful capability for qualitative analysis,while SOFM network can approach most problems fast and visualize result easily.By combing those advantages of the two theories,a system flow chart is designed and the work principles of each part are described.The validity of these models is tested by practical examples.The method can decrease the computation time,and visualize the result.Finally,the visualized topology-ordering map is obtained.
%K Rough Sets
%K SOFM Networks
%K Fault Diagnosis<br>粗糙集
%K SOFM网络
%K 故障诊断
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=DF055CD222923B34&yid=37904DC365DD7266&vid=EA389574707BDED3&iid=94C357A881DFC066&sid=3F0AF5EDBC960DB0&eid=4C100B7696CE9E24&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=3&reference_num=5