Fuzzy CBR based on Pattern Recognition and its Application

Zhao Quanming, Li Lingling, Li Zhigang, Wang Jiannan, Liu Fengguo
{"title":"Fuzzy CBR based on Pattern Recognition and its Application","authors":"Zhao Quanming, Li Lingling, Li Zhigang, Wang Jiannan, Liu Fengguo","doi":"10.1109/ICCIS.2006.252297","DOIUrl":null,"url":null,"abstract":"Case-based reasoning (CBR) has been widely applied in expert systems. This method can find out the solution of the problem to be solved in terms of the former experience by analyzing the similarity of information between the problem to be solved and the existing cases. However, among the information from the problem, some data are fuzzy. In order to find out the similar cases successfully, a method of fuzzy CBR based on pattern recognition is presented in this paper. According to this method, all the relative existing cases in the case database are fuzzed and each can be regarded as typical pattern. And then a new general closeness degree algorithm was constructed to deal with general and fuzzy data by combining two kinds of closeness degree algorithm and is used as the similarity degree function between the cases and the problem to be solved so as to realize case matching under the fuzzy strategy by using the method of pattern recognition. The validity of this method has been confirmed in electrical apparatus product design","PeriodicalId":296028,"journal":{"name":"2006 IEEE Conference on Cybernetics and Intelligent Systems","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE Conference on Cybernetics and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIS.2006.252297","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Case-based reasoning (CBR) has been widely applied in expert systems. This method can find out the solution of the problem to be solved in terms of the former experience by analyzing the similarity of information between the problem to be solved and the existing cases. However, among the information from the problem, some data are fuzzy. In order to find out the similar cases successfully, a method of fuzzy CBR based on pattern recognition is presented in this paper. According to this method, all the relative existing cases in the case database are fuzzed and each can be regarded as typical pattern. And then a new general closeness degree algorithm was constructed to deal with general and fuzzy data by combining two kinds of closeness degree algorithm and is used as the similarity degree function between the cases and the problem to be solved so as to realize case matching under the fuzzy strategy by using the method of pattern recognition. The validity of this method has been confirmed in electrical apparatus product design
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于模式识别的模糊CBR及其应用
案例推理(Case-based reasoning, CBR)在专家系统中有着广泛的应用。该方法通过分析待解决问题与已有案例信息的相似度,在已有经验的基础上找出待解决问题的解决方案。然而,在问题的信息中,有些数据是模糊的。为了成功地找出相似案例,本文提出了一种基于模式识别的模糊CBR方法。根据该方法,对案例库中所有相对存在的案例进行模糊处理,每个案例都可以视为典型模式。然后结合两种贴近度算法构造了一种新的通用贴近度算法来处理一般数据和模糊数据,并将其作为案例与待解决问题之间的相似度函数,利用模式识别的方法实现模糊策略下的案例匹配。该方法的有效性在电器产品设计中得到了验证
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Multi-layer Control Strategy of Dynamics Control System of Vehicle A Fuzzy Multiple Critera Decision Making Method Gait Recognition Considering Directions of Walking Nonlinear Diffusion Driven by Local Features for Image Denoising Designing of an Adaptive Adcock Array and Reducing the Effects of Other Transmitters, Unwanted Reflections and Noise
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1