https://github.com/urvee1810/air-quality-prediction-using-arima
Analyzed Beijing's air quality data using time series analysis and ARIMA modeling to forecast PM2.5 pollution levels. Identified seasonal patterns and correlations between pollutants, revealing insights into urban air quality trends and potential contributing factors.
https://github.com/urvee1810/air-quality-prediction-using-arima
arima-model dickey-fuller-test matplotlib numpy pandas python seaborn statistical-analysis time-series-analysis
Last synced: 4 months ago
JSON representation
Analyzed Beijing's air quality data using time series analysis and ARIMA modeling to forecast PM2.5 pollution levels. Identified seasonal patterns and correlations between pollutants, revealing insights into urban air quality trends and potential contributing factors.
- Host: GitHub
- URL: https://github.com/urvee1810/air-quality-prediction-using-arima
- Owner: Urvee1810
- Created: 2025-02-18T09:57:17.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-18T10:48:54.000Z (over 1 year ago)
- Last Synced: 2025-02-18T11:35:33.777Z (over 1 year ago)
- Topics: arima-model, dickey-fuller-test, matplotlib, numpy, pandas, python, seaborn, statistical-analysis, time-series-analysis
- Language: Jupyter Notebook
- Homepage:
- Size: 2.2 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0