A Rainy Outlook: Machine Learning Approaches for Predicting Precipitation

A Review of Rainfall Prediction Using Machine Learning and Deep Learning

Artificial Intelligence-driven extreme forecasting is particularly beneficial for systems dealing with localised and monsoon rainfall variability.

Daily rainfall prediction in Lagos using logistic regression, random forest, and support vector machine with web development

An end-to-end rainfall prediction pipeline tailored to the Lagos environment is provided and the practical value of coupling ML with accessible deployment frameworks for climate decision-making in developing countries is demonstrated.

Flood Risk Prediction Using Reservoir and Rainfall Data Based on Machine Learning Techniques

The experimental outcome reveals that tree-based ensemble models are more accurate in predicting the flood risk levels compared to the existing statistical models, especially when dealing with imbalanced datasets.

Using artificial intelligence for wind speed prediction

Accurate wind speed prediction is critical for renewable energy management, agriculture, and weather forecasting. This study investigates the use of machine learning techniques for predicting daily average wind speed using meteorological features, including rainfall, maximum and minimum temperature, grass minimum tempe...

Ensemble Machine Learning for Farm-Level Rainfall Forecasting Based on Satellite Observations

Evaluating and improving crop-yield forecasting methods during extreme drought

Light is shed on the effect of dissimilarity between train and test feature distributions on forecasting models, compares deep learning versus non-deep learning models, and introduces modifications that are effective for non-deep learning models.