A conceptual model for clustering local government areas using complex fuzzy sets
Identifying matched local government areas (LGAs) through indicators such as socio-demography, economic and industrial development, and environmental variables has significant effects on public service management. Profiling of LGAs can be a fundamental activity for cooperation between government authorities to assist in the coordination tasks and facilitate decision making in short or long term planning. However, regional profiles contain data with typical temporal and uncertain features which bring challenges to identify matched regions. In this paper, a conceptual model based on complex fuzzy sets has been presented which uses complex fuzzy sets to process the temporal and uncertain features simultaneously. The conceptual model was tested through a local government area clustering problem. Testing results indicate it is flexible and applicable to handle periodic and uncertain data.