Improvement design of fuzzy geo-demographic clustering using Artificial Bee Colony optimization

Geo-demographic analysis (GDA) is the study of geo-demographic that refers to spatial or geographical area, utilizing some spatial based analysis explicitly. Fuzzy Geographically Weighted Clustering (FGWC), a variant of Fuzzy C-Means (FCM), has been serving as an effective algorithm in Geo-demographic Analysis. FGWC is sensitive because of its initialization by determining random cluster centers makes the greater probability of clustering result falling into the local optima that affect the clustering quality. Artificial Bee Colony (ABC), one of metaheuristic algorithms is usually used as a global optimization tools. This research aims to propose a integration design of ABC based optimization and FGWC for improving geo-demographic clustering accuracy.