Intelligent decision support system of emergency language based on fog computing

Abstract

In recent years, various emergencies have frequently occurred worldwide, which has forced relevant service departments to pay more attention to decision-making and emergency management. Since emergency events are characterized by complex environments, unstable events, and time constraints, events usually involve multiple factors and promptly correct errors in the decision-making process. In fact, in many cases, emergency decision-making needs to select an optimal one from multiple alternatives for execution. The fog algorithm decision-making method can solve the problem of optimal solution selection, and it has been widely used in many fields. This article evaluates the emergencies that have occurred in the past 10 years. The evaluation indicators include direct economic loss, indirect reputation loss, ecological environment indicators, and healthy living indicators. The first two are cost-based indicators. The index value of direct economic loss and indirect reputation loss is as small as possible, while the index value of ecological environment index and healthy living index is the larger the better. Among the many selected emergencies, only the index evaluation scores of fires are reliable (P < 0.01), and the evaluation scores of other emergencies belonging to natural disasters are a bit wrong (P > 0.05). The reason for this may be that the direct economic losses caused by natural disasters are not well counted, and the families involved and the environment are too wide. Therefore, the emergency language intelligent decision support system based on fog computing has a good development prospect.