Authors: ndhuprakash M, Gokul R, Harishragavendra M, Parthasharathy R
Abstract: Weather prediction supports agriculture, transportation, travel planning, and public safety. This paper presents an Intelligent Weather Prediction System that combines machine learning techniques with an accessible application interface. The proposed workflow uses weather observations such as temperature, humidity, atmospheric pressure, wind speed, cloud cover, and rainfall, depending on the data source. It includes data collection, preprocessing, exploratory analysis, feature preparation, model training, evaluation, and presentation of predictions. Candidate models include regression methods for continuous weather variables, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Long Short-Term Memory (LSTM) for suitable classification, regression, or sequential forecasting tasks. The application may also provide AI-assisted weather question answering and concise weather-news summaries when these components are implemented and connected to reliable sources. The system is intended to make weather information easier to understand and use. Actual performance must be measured on the selected dataset; no accuracy result is claimed in this draft. The final paper should report the implemented models, dataset, evaluation results, and system screenshots
DOI: http://doi.org/
