A novel intuitionistic fuzzy clustering method for geo-demographic analysis

Authors:
Le Hoang Son;Bui Cong Cuong;Pier Luca Lanzi;Nguyen Tho Thong
Affiliations:
Hanoi University of Science, Vietnam National University, 334 Nguyen Trai, Thanh Xuan, Ha Noi, Viet Nam;Institute of Mathematics, Vietnamese Academy of Science and Technnology, 18 Hoang Quoc Viet, Cau Giay, Ha Noi, Viet Nam;Department of Electronics and Information, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133, Italy;Hanoi University of Science, Vietnam National University, 334 Nguyen Trai, Thanh Xuan, Ha Noi, Viet Nam
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

Geo-Demographic Analysis (GDA) is an important tool to explore the underlying rules that regulate our world, and therefore, it has been widely applied to the development of effective socio-economic policies through the analysis of data generated from Geographic Information Systems (GIS). In GDA applications, clustering plays a major role however, the current state-of-the-art algorithms, namely the Fuzzy Geographically Weighted Clustering (FGWC), have demonstrated several limitations both in terms of speed and in terms of quality of the achieved results. Accordingly, in this paper, we propose a novel clustering algorithm for GDA application, based on recent results regarding intuitionistic fuzzy sets and the possibilistic fuzzy C-means, that aims at overcoming some of the limitations of the existing methods.