About this document

CSE427 Report Paper01 by konodiosama69 is a document available to read on EtoBox.

This study presents a Dual-Task Framework for predicting Air Quality Index (AQI) using a large dataset of 805,021 historical records, comparing deep learning models like LSTM with traditional ensemble methods. The LSTM model outperformed the XGBoost baseline in capturing long-range temporal relationships, achieving significant accuracy improvements. The research highlights the importance of meteorological factors and the use of Explainable AI techniques for transparent environmental monitoring.

Author

konodiosama69

Language

EN