Risk Zoning of Cardiac Arrest in the Framework of the GIS and Metaheuristic Algorithms based on the Context Information

Cardiac arrest is a condition where the heart rate disappears completely from the heart is not pumping blood. In spite of the fact that the majority of the cardiac arrest cases of homes or hospitals will be reported، about 20 percent of the cardiac arrest cases will be occurred in public places. Several factors in the incidence of cardiac arrest are impressive. These factors include environmental، personal interests، context information are patient person profile data. Due to the fact that in the preparation of maps of these factors، use of geographic information system and spatial analysis. But due to the volume of the top layers of requirements، to analyze the underlying data accurate and efficiently take advantage of the powerful methods، such as the optimization algorithm has been suggested. In this study، the context information used including the environmental context information (such as land-use، distance from hospitals، elevation، the economic status of the area، and reported cases of cardiac) and person profile information (such as age، smoking and disease status) has been. For the evaluation of the study area and the dangerous places in the incidence of cardiac arrest from swarm intelligence algorithms include the ACO and PSO were used. Reason of this choice more easily using these methods، compliance with real world issues، the better modelling of uncertainly and so on. Due to the lack of data required within our country، the proposed model is typically run for public places was State of Pennsylvania Petersburg. The results of the research confirms the impact of context information in the abundant occurrence of cardiac arrest. For example changing in the people context information، is to lead to a change in the map class about 98 percent