摘要
随着全球环境问题日益严峻，传统环境监管手段已难以满足精准化、智能化管理需求，构建基于大数据技术的环境监管平台成为当前研究的重要方向。本研究旨在通过整合多源环境数据，运用大数据分析、云计算及人工智能等先进技术，设计并实现一个高效、智能的环境监管大数据平台。研究以提升环境监管效率和决策科学性为目标，采用模块化设计理念，构建了数据采集、存储、处理与可视化的核心功能体系，并结合机器学习算法实现了污染源识别、风险预警及趋势预测等功能。通过对实际环境数据的测试与验证，该平台展现出强大的数据处理能力和精准的分析效果，显著提高了环境监管工作的实时性和准确性。研究的主要创新点在于首次将多源异构数据融合与深度学习技术应用于环境监管领域，突破了传统方法在数据规模和复杂度上的限制。此外，平台的成功应用为环境治理提供了科学依据和技术支撑，具有重要的实践意义和推广价值，为未来智慧环保体系建设奠定了坚实基础。
关键词：环境监管；大数据平台；多源数据融合；深度学习；智能分析
Abstract
With the increasing severity of global environmental issues, traditional environmental supervision methods are no longer sufficient to meet the demands for precise and intelligent management. Consequently, constructing an environmental supervision platform based on big data technology has become a significant research direction. This study aims to design and implement an efficient and intelligent big-data-driven environmental supervision platform by integrating multisource environmental data and leveraging advanced technologies such as big data analytics, cloud computing, and artificial intelligence. Targeting the enhancement of supervisory efficiency and decision-making scientificity, the study adopts a modular design concept to establish a core functional system encompassing data acquisition, storage, processing, and visualization. Furthermore, machine learning algorithms are incorporated to achieve functionalities such as pollution source identification, risk warning, and trend prediction. Through testing and validation with real-world environmental data, the platform demonstrates robust data processing capabilities and precise analytical outcomes, significantly improving the timeliness and accuracy of environmental supervision work. A primary innovation of this research lies in its pioneering application of multisource heterogeneous data fusion and deep learning techniques in the field of environmental supervision, overcoming limitations of traditional methods in terms of data scale and complexity. Additionally, the successful implementation of the platform provides scientific evidence and technical support for environmental governance, showcasing substantial practical significance and promotion value while laying a solid foundation for the future construction of smart environmental protection systems.
Keywords：Environmental Regulation; Big Data Platform; Multi-Source Data Fusion; Deep Learning; Intelligent Analysis
目 录
摘要 I
Abstract II
一、绪论 1
(一) 环境监管大数据平台的研究背景 1
(二) 构建与应用的意义分析 1
(三) 国内外研究现状综述 1
(四) 本文研究方法与结构安排 2
二、环境监管大数据平台的构建基础 2
(一) 数据采集与整合技术框架 2
(二) 平台架构设计的关键要素 3
(三) 核心功能模块的构建思路 3
三、环境监管大数据平台的技术实现 4
(一) 数据存储与管理方案 4
(二) 数据分析与挖掘算法应用 4
(三) 可视化技术在平台中的实践 5
四、环境监管大数据平台的应用实践 6
(一) 污染源监测的实际案例分析 6
(二) 决策支持系统的运行效果评估 6
(三) 平台优化与未来发展方向探讨 7
结 论 8
参考文献 9
