GitHub Actions code for determining the watering amount needed based on met.hu and WeatherAPI.

Python framework for short-term ensemble prediction systems.

This QuickApp predicts the rain in Europe with data from the Buienradar, two hours in advance

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.

ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.

Rainfall prediction

cloud burst prediction website rendered using streamlit from a pretrained ml model

A project aiming at delevering tools for visualisation and analysis of Barcelona rainfall data. Data is retrieved from there: https://opendata-ajuntament.barcelona.cat/data/en/dataset/precipitacio-hist-bcn.

ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.

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

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

Completed for the "Laboratory of Computational Physics Mod. B" under the supervision of Professor Carlo Albert. The project utilizes Keras in TensorFlow for implementation.

Used different Transformer based and LSTM based models for forecasting rainfall in different areas of Mumbai. Employed different smart training techniques to improve correlation with the true time-series.

Rainfall Prediction App is an application designed to predict rainfall in the Banyuasin Regency, Indonesia. This project serves as a final project developed to complete the undergraduate program at the University of Sriwijaya. The method employed involves the Tsukamoto Fuzzy Inference System optimized using genetic algorithms.

The project aimed to enhance the accuracy of weather and rainfall prediction using machine learning techniques. Leveraging a dataset from Kaggle as a starting point, the team focused on data preprocessing to improve model performance.

The Crop Management System is a machine learning-based project designed to provide predictions and recommendations for farmers.

ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.

Rainfall Weather Analysis

This is a rainfall prediction classification using R programming.

Predicted rainfall using different classification algorithms