动态因果建模和在线协作预测香港和澳门的空气质量
Cheng He1, Jia Ren2,3, Wenjian Liu1
1Faculty of Data Science, City University of Macau, Macao 999078, China.
Entropy (Basel, Switzerland)
|September 28, 2023
概括
这项研究使用动态贝叶斯网络来模拟香港和澳门的空气质量,揭示了污染及其驱动因素之间的因果关系. 这种方法有助于有效预测和管理大气环境.
科学领域:
- 环境科学 环境科学
- 大气化学 大气化学
- 数据科学数据科学数据科学
背景情况:
- 由于城市化和人口密度,香港和澳门面临空气质量挑战.
- 在广东-香港-澳门大湾区,大气环境健康至关重要.
- 多种因素导致了复杂的空气污染动态.
研究的目的:
- 构建香港和澳门空气质量的动态因果模型.
- 研究气象学与空气质量之间的相互作用.
- 为了实现协作预测和污染警告.
主要方法:
- 应用一个可解释的动态贝叶斯网络 (DBN).
- 构建空气质量的动态因果模型.
- 因果关系的定性和定量分析.
主要成果:
- 成功开发了一个基于DBN的动态因果模型.
- 确定了气象和空气质量之间的动态相互作用.
- 评估了污染物和决定因素之间的因果关系.
- 促进了空气污染物度的在线协作预测.
结论:
- DBN模型有效地解释和管理复杂的大气环境系统.
- 该研究为香港和澳门的空气质量管理提供了关键的见解.
- 这些发现适用于具有相似背景的邻近地区.
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