基于LSTM模型的空气质量指数预测

Air Quality Index Prediction Based on LSTM Models

摘要: 随着经济的飞速发展和人类活动的日益频繁，环境问题逐渐成为全球关注的焦点，其中空气质量问题尤为突出。空气中污染物的种类和浓度不断增加，对人类健康和生态环境造成了严重威胁。本文基于LSTM模型来预测未来空气质量，使用处理后的数据对模型进行训练，确保模型的预测性能满足要求。准确计算和预测空气质量等级，能够及时向公众发布空气质量信息，引导公众采取有效的防护措施，减少污染物对健康的危害。此外，为环境管理部门制定科学合理的环境政策提供依据，有助于推动空气质量的改善。

Abstract: With rapid economic development and increasingly frequent human activities, environmental issues have gradually become a global focus, with air quality problems being particularly prominent. The types and concentrations of air pollutants continue to increase, posing a serious threat to human health and the ecological environment. This paper employs an LSTM model to forecast future air quality, training the model using processed data to ensure its predictive performance meets requirements. Accurate calculation and prediction of air quality levels enable timely dissemination of air quality information to the public, guiding individuals to take effective protective measures and reducing the health hazards posed by pollutants. Furthermore, it provides a basis for environmental management departments to formulate scientifically sound environmental policies, thereby contributing to the improvement of air quality.