城市环境监测和健康风险评估,引入模糊智能计算模型
Weijia Wang1, Xin Guan2, Xiaoyan Peng3
1School of Information Technology, Deakin University, Geelong, VIC, Australia.
Frontiers in public health
|June 21, 2024
概括
这项研究开发了一种新的模糊智能计算模型,用于使用环境数据评估城市健康风险. 该模型准确地估计了风险,显示PM2.5
科学领域:
- 环境健康 环境健康
- 智能计算是一种智能计算.
- 城市规划 城市规划
背景情况:
- 城市环境带来复杂的健康风险.
- 评估这些风险需要复杂的评估工具.
- 现有的方法在不同的条件下可能缺乏精度.
研究的目的:
- 介绍一个新的模糊智能计算模型.
- 提高城市健康风险评估的准确性.
- 使用多媒体环境监测数据.
主要方法:
- 采用了一个模糊推理系统 (FIS) 模型.
- 综合的多媒体环境数据 (PM2.5,噪声,IAQI,TCI,NPI).
- 在三个不同污染水平的城市 (北京,昆明,无锡) 验证了该模型.
主要成果:
- 该模型准确估计了健康风险 (高R2值:0.89-0.92).
- 在PM2.5和健康风险之间发现了正相关性;噪音影响因城市而异.
- 模型表现出高准确度 (低RMSE) 和可信度 (关键指数p<0.05).
结论:
- 模糊智能模型有效地评估不同环境中的城市健康风险.
- 这些发现支持加强环境保护和健康管理战略.
- 提供可持续城市发展和规划的科学基础.
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