Title :
Fuzzy hierarchical clustering based on fuzzy dissimilarity
Author :
Lv, Y.Q. ; Lee, C.K.M.
Author_Institution :
Sch. of Mech. & Aerosp. Eng., Nanyang Technol. Univ., Singapore, Singapore
Abstract :
This paper develops a new fuzzy hierarchical clustering method based on Agglomerative nesting with the introduction of fuzzy dissimilarity. Since normal hierarchical clustering methods only can be applied for real numbers while a set of possible values, fuzzy numbers are gathered in data collection. It´s important to find an effective and efficient way for clustering so as to realize the structure of the complex data for decision making. In this research, the trapezoidal fuzzy numbers are selected in this research, and the proposed new hierarchical clustering method can be competent with the existing clustering method with the given set of fuzzy numbers.
Keywords :
decision making; fuzzy set theory; pattern clustering; decision making; fuzzy dissimilarity; fuzzy hierarchical clustering; fuzzy numbers; Artificial intelligence; Clustering algorithms; Clustering methods; Companies; Decision making; Manufacturing systems; Fuzzy Dissimilarity; Fuzzy Hierarchical Clustering; Fuzzy Number; Graded Mean Integration Representation (GMIR);
Conference_Titel :
Industrial Engineering and Engineering Management (IEEM), 2011 IEEE International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4577-0740-7
Electronic_ISBN :
2157-3611
DOI :
10.1109/IEEM.2011.6118070