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人工智能大模型和文本挖掘驱动的城市绿化政策分析框架
Li Li1,2, Xuesong Yang3, Sijia Liu4
1School of Urban Design, Wuhan University, Wuhan, 430072, China.
Scientific reports
|August 12, 2025
概括
这项研究引入了一个基于人工智能的框架,用于分析城市绿化政策,克服传统偏见. 它使得系统的,实时的评估和跟踪政策演变,以实现更智能的城市规划.
科学领域:
- 环境政策 环境政策
- 城市规划 城市规划
- 人工智能的人工智能
背景情况:
- 传统的政策分析有个人的偏见和有限的范围.
- 文本挖掘提供了效率,但在城市绿化政策分析中未得到充分利用.
- 现有的研究缺乏系统分析和实时政策跟踪.
研究的目的:
- 利用人工智能和文本挖掘开发一个多维的动态政策分析框架.
- 系统地评估城市绿化政策,跟踪其演变,并解释结果.
- 实现实时政策跟踪和可视化,以改善城市规划.
主要方法:
- 构建了一个新的框架,集成AI大模型和文本挖掘.
- 应用框架来分析武汉15年城市绿化政策.
- 分析了政策主题的演变,年度主题分布和绿化指标的变化.
主要成果:
- 揭示了15年来武汉绿化政策的重大变化.
- 确定了从基本的绿化转向生态修复的政策转变.
- 观察到重点从花规划到湿地保护的转变.
结论:
- 由人工智能驱动的框架为智能政策评估提供了一个新的范式.
- 这种方法提高了政策制定和实施的效率和准确性.
- 这种方法对于开发具有适应性和理性政策的智慧城市至关重要.
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