%0 Journal Article %T 基于人工智能、大数据技术在智慧城市基层治理的应用与分析
Application and Analysis of Artificial Intelligence and Big Data Technology in Grassroots Governance of Smart Cities %A 范建 %A 刘京 %A 武建双 %A 何君 %A 郭少奇 %A 孙园 %A 余婷 %A 郭扬涌 %A 卢康 %J Artificial Intelligence and Robotics Research %P 427-438 %@ 2326-3423 %D 2025 %I Hans Publishing %R 10.12677/airr.2025.142042 %X 为深化新时代基层治理创新，根据国务院办公厅印发的《关于乡村加强和改进治理的指导意见》，2035年城乡公共服务、管理、安全保障需显著提升，实现基层治理活力、和谐有序，治理体系和治理能力基本现代化。随着信息技术的迅猛推进，如何有效融合大数据与人工智能等尖端科技，以辅助智慧城市基层治理体系的现代化建设，实现高效、智能的管理目标，已成为当前亟待深入思考与探索的重要议题。本文深入探讨了人工智能(AI)和大数据技术在智慧城市基层治理中的应用，通过结合大数据、NLP、深度学习神经网络等前沿技术，设计并实现了一套高效的基层治理平台。该平台通过智能识别、数据分析和全景展示等功能，实现了对城市治理的智能化、精细化管理。具体研究成果包括：利用卷积循环神经网络(CRNN)提高图像识别精度，通过大数据ETL技术构建多样化数据集，以及实现网格管理、事件管理和全景分析等多个核心业务模块的智能化升级。这些创新不仅显著提升了管理效率和监督效能，还为城市规划和治理提供了科学依据。
In order to deepen the innovation of grass-roots governance in the new era, according to the guidance on strengthening and improving governance in rural areas issued by the general office of the State Council, urban and rural public services, management and security need to be significantly improved in 2035, so as to realize the vitality, harmony and order of grass-roots governance, and the basic modernization of governance system and governance capacity. With the rapid development of information technology, how to effectively integrate cutting-edge technologies such as big data and artificial intelligence to assist the modernization of the grass-roots governance system of smart cities and achieve the goal of efficient and intelligent management has become an important issue to be considered and explored. This paper discusses the application of artificial intelligence (AI) and big data technology in the grassroots governance of smart cities NLP, Deep learning neural network and other cutting-edge technologies, designed and implemented a set of efficient grass-roots governance platform. Through the functions of intelligent identification, data analysis and panoramic display, the platform realizes the intelligent and refined management of urban governance. The specific research results include: Using Convolutional recurrent neural network (CRNN) to improve the accuracy of image recognition, building diversified data sets through big data ETL Technology, and realizing the intelligent upgrading of multiple core business modules such as grid management, event management and panoramic analysis. These innovations not only significantly improve the management efficiency and supervision efficiency, but also provide a scientific basis for urban planning and governance. %K 人工智能， %K 基层治理， %K 大数据， %K NLP， %K 深度学习神经网络
Artificial Intelligence %K Grassroots Governance %K Big Data %K NLP %K Deep Learning Neural Network %U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=110190