Popular GitHub Repositories for Rainfall

Rainfall Prediction using Machine Learning. India Rainfall Prediction for 115 years. Rainfall Project with Code and Documents

The proposed system will be able to predict the crop yield production which will be useful to farmers for harvesting and storage. The system will use the weather forecasting which includes the parameters like temperature, rainfall, humidity, dew point and the normalized difference vegetation index time series from Sentinel-2 satellite for selected region. By using both the results obtained,accurate crop yield prediction can be calculated which will help farmers in planning efficiently, minimize costs and maximize yields—and profits—as a result.

Rainfall prediction is one of the challenging tasks in weather forecasting process. Accurate rainfall prediction is now more difficult than before due to the extreme climate variations. Machine learning techniques can predict rainfall by extracting hidden patterns from historical weather data.

Rainfall prediction from Australian weather dataset using multiple machine learning models.

Time series forecasting solution for predicting agricultural climate variables in Harveston using ensemble LightGBM models with advanced feature engineering. Our approach combines temporal, geographical, and meteorological features to accurately predict temperature, radiation, rainfall, and wind patterns for agricultural planning.

Create a comprehensive full-stack project that utilizes Artificial Intelligence (AI) to predict rainfall and provides a user-friendly interface for users to interact with. The project aims to leverage machine learning algorithms and data visualization techniques to provide accurate rain predictions, helping individuals and organizations make inform

Time series forecasting solution for predicting agricultural climate variables in Harveston using ensemble LightGBM models with advanced feature engineering. Our approach combines temporal, geographical, and meteorological features to accurately predict temperature, radiation, rainfall, and wind patterns for agricultural planning.

Server-side data pipeline for the PluvIA mobile app. Periodically scrapes rainfall data from AESA-PB, enriches it with location metadata and AI-based forecasts, and stores it in MongoDB for offline access by the app. Powered by n8n and Docker.

Application of the ARIMA model to forecast PET patterns. Leveraging time-series analysis techniques, it predicts future rainfall levels by analyzing historical data specifically from Bahawalnagar District, Punjab, Pakistan.