文献类型：会议论文

英文题名：Fuzzy Discrimination Analysis Method Based on RBFNN and Its Application in Soft Measurement

作者：Gao Lin[1,2];Liu Xi-Mei[1,2];Gu Xing-Sheng[1];Sui Yuan-Yuan[2];Zhuang Ke-Yu[2]

机构：[1]East China Univ Sci & Technol, Shanghai 200237, Peoples R China;[2]Qingdao Univ Sci & Tchnol, Qingdao, Peoples R China

会议论文集：IEEE International Conference on Automation and Logistics

会议日期：SEP 01-03, 2008

会议地点：Qingdao, PEOPLES R CHINA

语种：英文

外文关键词：Artificial Neural Networks; Fuzzy sets; RBFNN; Discrimination analysis; Soft measurement

摘要：Artificial Neural Networks(ANN) has being used widely in information processing, intelligence control because of its abilities of self-organization,self-learning and parallel-processing. The work to use ANN theory and Fuzzy sets together to solve the practical problem is being promoted with the Fuzzy sets birth and development. Based on the basic theory of RBFNN and Fuzzy sets,a new fuzzy discrimination analysis method named RFD(Fuzzy Discrimination based on RBFNN) is proposed in this paper. It includes three steps to construct RFD, that is classification earmark, modeling by RBFNN and Fuzzy reasoning. After explaining in detail the process of the above three Steps to construct RFD, It is tested for discriminating some UCIs such as the IRIS data and a practical soft measurement data. The results indicate that RFD has low error- discrimination percentage, short discrimination time and satisfied practical application effect.