Emergency Resource Planning by Using Spatial Data Association Rule Mining and Linear Programming Method

Abstract

Spatial attributes are important factors that affect the whole process of emergency events. However, studies on this subject have not sufficiently been carried out. This paper presents a new idea that incorporates spatial predicates describing the spatial relationships between emergency locations and surrounding objects into emergency event analysis. Furthemore, a multi-level spatial data association algorithm is developed to realize knowledge discovery for emergency event analysis. Traditional linear programming model failed to give reasonable weight for different emergency events ocured in different locations. While this paper uses spatial data assocation rules which detect how spatial attributes affect emergency events as the weighting mechanism for different spots, Based on such method, we finally propose a linear programming method that realize emergency resource planning in a new perspective.