用人工智能预测和优化空气质量指数
Muhammad Mubeen1, Shuwei He1, M Safiur Rahman2
1College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China.
Journal of environmental sciences (China)
|August 21, 2025
概括
通过中国的监测数据, 人工智能提高了空气质量预测. 这种智能预测和优化方法改善了管理策略,并预测了改善空气质量的未来趋势.
科学领域:
- 环境科学
- 数据科学
- 大气化学
背景情况:
- 由于工业排放,汽车排放和沙等自然来源,空气污染是一个重大的环境问题.
- 主要污染物包括二氧化硫 (SO2),二氧化 (NO2),氨离子 (NH4+),黑碳,臭氧和细颗粒物 (PM2.5).
- 有效的空气质量管理和预测对于公众健康和环境保护至关重要.
研究的目的:
- 利用来自中国的广泛监测数据,提高空气质量预测和管理的人工智能 (AI).
- 开发先进的人工智能模型,准确评估空气质量状况和未来的趋势.
- 创建一个智能空气质量指数 (AQI) 以快速评估和对敏感群体的影响评估.
主要方法:
- 利用来自中国四个地区的大量空气质量监测数据 (2021年8月至2022年7月).
- 应用各种建模技术和机器学习方法,包括智能预测和优化 (SPO) 方法.
- 训练有素的人工智能模型分析污染物度和预测空气质量指数.
主要成果:
- 人工智能模型在空气质量预测方面取得了很高的准确性 (约99%).
- 这项研究发现,有很大一部分不健康的空气质量影响敏感人群.
- SPO的方法证明了对监测数据的有效利用.
结论:
- 人工智能为防止空气污染和改善空气质量提供了有效的策略.
- 准确的空气质量预测对于缓解不利气候条件和保护公共健康至关重要.
- 开发的智能AQI为环境管理和政策制定提供了宝贵的见解.
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