The intelligent decision-making process construction of emergency intelligence based on the big data

ABSTRACT

Global public emergencies represented by COVID-19 have posed new requirements and challenges to the current governance systems and capacities of governments. Mining decision-level intelligence from massive, multi-source and heterogeneous big data is the basic environment of current emergency decision making. This paper is based on the case analysis of COVID-19 epidemic prevention and control and constructs the intelligent decision-making process framework of emergency intelligence from the basic support layer, information and data layer, fusion output layer, emergency decision-making layer and main user layer. A risk governance system of "government-led, enterprise participation, media coordination, social crowdsourcing"has been established with big data co-construction and sharing and joint epidemic prevention and control. Through intelligence collection, processing, analysis and output transmission of epidemic-related data and information in the big data environment, it provides services for the emergency prevention and control of major epidemics in both normal and abnormal situations. In the front-end control phase, the emergency intelligence perception of the source quality is ensured to support the emergency decision, and the wisdom level of emergency decision-making is improved by optimizing the use of terminal intelligence and failure prevention methods. This paper proposes to optimize the intelligent decision-making process of emergencies from the effective prevention strategy of intelligence perception failure and the effective intervention strategy of decision failure prevention. This article explores the big data in the application of global public emergency management and innovation, change and revelation, to expand the emergency decision-making from the perspective of intelligence applications, provides with wisdom for the government emergency decision. © 2022 ACM.