medAli-ai/Beijing-air-quality-prediction-internship
This project has applied Machine Learning and Deep Learning techniques to analyse and predict the Air Quality in Beijing.
This project helps environmental agencies or urban planners predict Beijing's hourly PM2.5 air pollutant concentration one hour into the future. It takes historical hourly air quality and meteorological data as input and provides an anticipated PM2.5 level. This tool is for environmental scientists, urban planners, or public health officials monitoring and forecasting air pollution.
No commits in the last 6 months.
Use this if you need to forecast short-term PM2.5 air quality in Beijing based on historical environmental data.
Not ideal if you need to predict air quality for other regions or require forecasts for longer time horizons beyond one hour.
Stars
16
Forks
1
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Sep 19, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/medAli-ai/Beijing-air-quality-prediction-internship"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
tallamjr/astronet
Efficient Deep Learning for Real-time Classification of Astronomical Transients and Multivariate...
AIStream-Peelout/flow_tutorials
Public tutorials of using Flow Forecast for forecasting and classifying time series data
chris-santiago/tsfeast
A collection of Scikit-Learn compatible time series transformers and tools.
jman4162/deep-time-series-forecasting
Comprehensive guide to time series forecasting using deep learning techniques, with practical...