The intelligent decision-making process construction of emergency intelligence based on the big data: -taking the epidemic prevention and control of COVID-19 as an example

Qinying Sun, Haiqun Ma
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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.
基于大数据的应急智能智能决策流程构建——以新冠肺炎疫情防控为例
以2019冠状病毒病为代表的全球突发公共事件对各国政府现有治理体系和治理能力提出了新的要求和挑战。从海量、多源、异构的大数据中挖掘决策级智能是当前应急决策的基本环境。本文基于COVID-19疫情防控案例分析,从基础支持层、信息数据层、融合输出层、应急决策层和主要用户层构建了应急智能决策流程框架。建立了“政府主导、企业参与、媒体协同、社会众包”的大数据共建共享、联防联控的风险治理体系。通过大数据环境下疫情相关数据信息的情报采集、处理、分析和输出传输,为正常和异常情况下的重大疫情应急防控提供服务。在前端控制阶段,保证对源质量的应急智能感知,支持应急决策,并通过优化使用终端智能和故障预防方法,提高应急决策的智慧水平。本文从智能感知失效的有效预防策略和决策失效预防的有效干预策略两方面提出了优化突发事件智能决策过程的方法。本文探讨大数据在全球公共应急管理中的应用与创新、变革与启示,从智能化的角度拓展应急决策的应用,为政府应急决策提供智慧。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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