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基于多模态融合和人工智能算法的紧急信息通信结构。

Emergency Information Communication Structure by Using Multimodel Fusion and Artificial Intelligence Algorithm.

机构信息

School of Political Science and Public Administration, East China University of Political Science and Law, Shanghai 201620, China.

出版信息

Comput Intell Neurosci. 2022 Oct 10;2022:3029039. doi: 10.1155/2022/3029039. eCollection 2022.

Abstract

With the development of The Times, social events are increasing, and emergency management has gradually become the main helper to solve the crisis in the public domain. By observing the current situation of many countries and regions, we can find that various types of public crises often occur in many countries and regions in the world, which have severely affected people's daily life, lives, and property. Through long-term research and analysis, it can be known that the emergency management mechanism currently established in China has certain shortcomings. The communication problem of emergency information is likely to cause the emergency work to not proceed smoothly. In addition, problems in the communication channels of emergency information are likely to cause problems in the cooperation of various departments when people carry out emergency management work, and the efficiency of the government in dealing with problems will also be reduced in real scenarios. In order to improve the efficiency of emergency information management, this paper aims at the various problems existing and facing in the construction of emergency management system. On this basis, the integration of various relevant emergency information management plan models is analyzed and sorted out, and based on the research and integration of the development of artificial intelligence algorithms. The main research results of emergency information management at home and abroad are comprehensively studied and evaluated. Finally, a QG algorithm based on more model fusion is developed. In the process of analysis, this article uses artificial intelligence algorithms to build a prediction model of multiple modes and collects the data needed to build the model by random extraction. Through the analysis of different data sets, it is used as the basic training data for prediction. Through comprehensive analysis, the model constructed in this paper can promote the sharing of emergency information among departments to a certain extent.

摘要

随着时代的发展,社会事件日益增多,应急管理逐渐成为解决公共领域危机的主要助力。通过观察许多国家和地区的现状,可以发现世界上许多国家和地区经常发生各种类型的公共危机,这些危机严重影响了人们的日常生活、生命和财产。通过长期的研究和分析,可以知道中国目前建立的应急管理机制存在一定的缺陷。应急信息的沟通问题可能导致应急工作无法顺利进行。此外,应急信息沟通渠道存在问题,可能导致人们在开展应急管理工作时各部门之间的合作出现问题,政府在实际场景中处理问题的效率也会降低。为了提高应急信息管理的效率,本文针对应急管理系统建设中存在的各种问题和面临的问题,对各种相关应急信息管理方案模型进行了分析和整理,并在研究和整合人工智能算法发展的基础上,对国内外应急信息管理的主要研究成果进行了全面研究和评价。最后,开发了一种基于更多模型融合的 QG 算法。在分析过程中,本文使用人工智能算法构建了多种模式的预测模型,并通过随机提取收集模型构建所需的数据。通过对不同数据集的分析,将其作为预测的基本训练数据。通过综合分析,本文构建的模型可以在一定程度上促进部门之间应急信息的共享。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d6a/9576386/13abdf3e61a4/CIN2022-3029039.001.jpg

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