摘 要：随着大数据技术的迅猛发展，其在公共事业决策中的应用潜力日益凸显。本研究旨在探索如何利用大数据分析方法优化公共事业决策过程，以提升决策的科学性和精准性。研究基于多源数据整合与挖掘技术，构建了面向公共事业的大数据分析框架，并结合机器学习算法对实际案例进行建模分析。通过对比传统决策模式，研究发现大数据驱动的方法能够显著提高资源分配效率和政策实施效果。创新点在于提出了融合时空特征的决策支持模型，有效解决了复杂场景下的动态优化问题。此外，研究还验证了该模型在交通管理、医疗资源配置等领域的适用性，为相关领域提供了理论参考和技术支撑。最终结论表明，大数据技术的应用不仅能够增强公共事业决策的透明度，还能促进社会治理水平的整体提升。
关键词：大数据分析；公共事业决策；多源数据整合
Abstract：With the rapid development of big data technology, its potential in public sector decision-making is becoming increasingly prominent. This study aims to explore how big data analytics can optimize the decision-making process in public sectors to enhance the scientific rigor and precision of decisions. Based on multi-source data integration and mining techniques, a big data analytics fr amework tailored for public sector applications was constructed, incorporating machine learning algorithms for modeling and analyzing real-world cases. By comparing with traditional decision-making approaches, it was found that big data-driven methods significantly improve the efficiency of resource allocation and the effectiveness of policy implementation. The innovation lies in the proposal of a decision support model that integrates spatiotemporal features, effectively addressing dynamic optimization challenges in complex scenarios. Furthermore, the applicability of this model was validated in domains such as traffic management and medical resource allocation, providing theoretical references and technical support for related fields. The final conclusion indicates that the application of big data technology not only enhances the transparency of public sector decision-making but also promotes an overall improvement in social governance capabilities.
引言 1
一、大数据与公共事业决策基础 1
(一)大数据技术概述 1
(二)公共事业决策特点 2
(三)数据驱动决策的意义 2
二、大数据分析方法在公共事业中的应用 3
(一)数据采集与预处理 3
(二)数据挖掘算法选择 3
(三)决策模型构建 4
三、基于大数据的公共事业决策优化策略 4
(一)优化目标设定 4
(二)关键影响因素分析 5
(三)策略实施路径 5
四、实证研究与案例分析 6
(一)案例背景介绍 6
(二)数据分析过程 6
(三)结果评估与反思 7
结论 7
参考文献 8
致谢 8
关键词：大数据分析；公共事业决策；多源数据整合
Abstract：With the rapid development of big data technology, its potential in public sector decision-making is becoming increasingly prominent. This study aims to explore how big data analytics can optimize the decision-making process in public sectors to enhance the scientific rigor and precision of decisions. Based on multi-source data integration and mining techniques, a big data analytics fr amework tailored for public sector applications was constructed, incorporating machine learning algorithms for modeling and analyzing real-world cases. By comparing with traditional decision-making approaches, it was found that big data-driven methods significantly improve the efficiency of resource allocation and the effectiveness of policy implementation. The innovation lies in the proposal of a decision support model that integrates spatiotemporal features, effectively addressing dynamic optimization challenges in complex scenarios. Furthermore, the applicability of this model was validated in domains such as traffic management and medical resource allocation, providing theoretical references and technical support for related fields. The final conclusion indicates that the application of big data technology not only enhances the transparency of public sector decision-making but also promotes an overall improvement in social governance capabilities.
Keywords: Big Data Analysis；Public Utility Decision Making；Multi-Source Data Integration
引言 1
一、大数据与公共事业决策基础 1
(一)大数据技术概述 1
(二)公共事业决策特点 2
(三)数据驱动决策的意义 2
二、大数据分析方法在公共事业中的应用 3
(一)数据采集与预处理 3
(二)数据挖掘算法选择 3
(三)决策模型构建 4
三、基于大数据的公共事业决策优化策略 4
(一)优化目标设定 4
(二)关键影响因素分析 5
(三)策略实施路径 5
四、实证研究与案例分析 6
(一)案例背景介绍 6
(二)数据分析过程 6
(三)结果评估与反思 7
结论 7
参考文献 8
致谢 8
