grtvishnu / air-pollution-prediction-and-forecasting

:octocat: Detection and Prediction of Air quality Index :octocat:

AIR POLLUTION FORECASTING AND PREDICTION

MODELS ✨

⚡️Models for Prediction:

• Random Forest - Random forests or random decision forests are an ensemble learning method for classification, regression.
• XGBoost - XGBoost is an open-source software library which provides a gradient boosting.
• Deep Learning - Multilayer Perceptron, Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning.
• CatBoost - CatBoost is an open-source gradient boosting on decision trees library with categorical features support out of the box.

🌈Models For Forecasting:

• LSTM- A Deep Learning method to find Future values of AQI upto 7 days
• Prophet - a package developed by facebook

🔥Features:

• Temperature (°C)
• Wind Speed (Km/h)
• Pressure (Pa)
• NO2 (ppm)
• Rainfall (Cm)
• PM10 (μg/m3)
• PM2.5 (μg/m3)
• AQI

📦 Used Packages

1. caret
2. tidyverse
3. tidymodels
4. randomforest
5. xgboost
6. data.table
7. Hmisc
8. catboost
9. VIM
10. Shiny

Prediction Data 📝

Forecast Data 📝

Interface 🔮

🚀 Interface Using shiny: Shiny is an R package that makes it easy to build interactive web apps straight from R.it is used for showing the insight of the data and prediction.

Collaborators

Vishnu Unnikrishnan 💻 🎨

Sruthy K S 💻 🎨

Teslin Rose 💻 🎨

Vini 💻 🎨

Happy Coding ❤︎

air-pollution-prediction-and-forecasting's Issues

Time series Combine LSTM and VAR

https://towardsdatascience.com/combine-lstm-and-var-for-multivariate-time-series-forecasting-abdcb3c7939b?gi=eab0b02cf7b1

UI and DashBoard

https://towardsdatascience.com/dashboards-are-dead-b9f12eeb2ad2

P value

https://towardsdatascience.com/defining-the-p-value-for-everyone-9103130f4fc2

Wrangle

https://towardsdatascience.com/the-basics-of-data-prep-7bb5f3af77ac

CatBoost Forecasting

https://medium.com/analytics-vidhya/catboost-for-forecasting-pm2-5-concentration-in-beijing-e0e972a11e1d