期刊論文

標題 An Approach for Fuzzy Modeling based on Self-Organizing Feature Maps Neural Network
學年 102
學期 2
出版(發表)日期 2014/05/01
作品名稱 An Approach for Fuzzy Modeling based on Self-Organizing Feature Maps Neural Network
作品名稱(其他語言)
著者 Chen, Ching-yi; Chiang, Jen-Shiun; Chen, K. Y.; Liu, T. K.; Wong, Ching-Chang
單位 淡江大學電機工程學系
出版者 Bahrain: Natural Sciences Publishing Corporation
著錄名稱、卷期、頁數 Applied Mathematics & Information Sciences 8(3), pp.1207-1215
摘要 Exploration of large and high-dimensional data sets is one of the main problems in data analysis. Self-organizing feature maps (SOFM) is a powerful technique for clustering analysis and data mining. Competitive learning in the SOFM training process focuses on finding a neuron that its weight vector is most similar to that of an input vector. SOFM can be used to map large data sets to a simpler, usually one or two-dimensional topological structure. In this paper, we present a new approach to acquisition of initial fuzzy rules using SOFM learning algorithm, not only for its vector feature, but also for its topological. In general, fuzzy modeling requires two stages: structure identification and parameter learning. First, the algorithm partitions the input space into some local regions by using SOFM, then it determines the decision boundaries for local input regions, and finally, based on the decision boundaries, it learns the fuzzy rule for each local region by recursive least squares algorithm. The simulation results show that the proposed method can provide good model structure for fuzzy modeling and has high computing efficiency.
關鍵字
語言 英文(美國)
ISSN 2325-0399
期刊性質 國外
收錄於 SCI;
產學合作
通訊作者
審稿制度
國別 巴林
公開徵稿
出版型式 電子版