Jia Dian, Wu Zhaoyang
School of Economics and ManagementQinghai Nationalities University Xining 810007 China.
School of Economics and ManagementQinghai Normal University Xining 810016 China.
IEEE Access. 2020 Oct 20;8:199646-199653. doi: 10.1109/ACCESS.2020.3032462. eCollection 2020.
With the deepening of the global economic community, various emergencies emerge in endlessly, and the risks gradually increase. People's lives and property are threatened, which also causes a great burden on the social economy. Hitherto unknown novel coronavirus events occurred in China after the outbreak of the new coronavirus in 2019. The emergency management system is not perfect, so we start to study and improve the deficiencies of the emergency management system, but it is still difficult to effectively prevent and deal with all kinds of sudden and frequent social problems. Therefore, this paper puts forward the research of intelligent evaluation system of government emergency management based on BP neural network. In this paper, an intelligent evaluation system of government emergency management based on Internet of things environment is established, and then the system is deepened by BP neural network algorithm to avoid the interference of human factors. An objective intelligent evaluation system of government emergency management is constructed and verified by an example. We applied the system in a province, and proved that the system has strong executive ability, outstanding big data computing ability, and can objectively evaluate and analyze the government emergency management. The operability and accuracy of the intelligent evaluation system are verified. The effective evaluation content provides a new idea and method for government emergency management. And then continuously improve the emergency management measures to achieve the effect of dealing with things smoothly without panic.
随着全球经济一体化的深入，各类突发事件层出不穷，风险也逐渐加大。人民生命财产受到威胁，这也给社会经济造成了巨大负担。2019年新型冠状病毒爆发后，中国发生了前所未有的新冠病毒事件。应急管理体系不完善，因此我们开始研究并改进应急管理体系的不足，但仍难以有效预防和应对各类突发频发的社会问题。因此，本文提出基于BP神经网络的政府应急管理智能评估系统的研究。本文构建了基于物联网环境的政府应急管理智能评估系统，然后通过BP神经网络算法对该系统进行深化，以避免人为因素的干扰。构建了一个客观的政府应急管理智能评估系统，并通过实例进行了验证。我们将该系统应用于某省，证明该系统具有较强的执行力、出色的大数据计算能力，能够对政府应急管理进行客观评估和分析。验证了智能评估系统的可操作性和准确性。有效的评估内容为政府应急管理提供了新的思路和方法。进而不断完善应急管理措施，达到遇事不乱、从容应对的效果。
