Prediction of Rainfall

Keywords: Rainfall

Background

Accurate prediction of rainfall is essential for various sectors, including agriculture, water resource management, and disaster preparedness. Traditional methods of rainfall prediction often rely on statistical models, but Artificial Neural Networks (ANN) have emerged as a promising approach due to their ability to capture complex relationships in the data. The target column here is Rain Tomorrow. The major challenge faced in predicting rainfall is to understand the non-linear relationship between the various features among data. The goal is to develop an accurate rainfall prediction model using ANN to forecast precipitation levels based on meteorological variables. The results obtained using ANN for rainfall prediction showed promising accuracy levels, with the model successfully capturing the underlying patterns and variations in precipitation.

Aim & Objectives

Aim
To Predict the rainfall using DL Techniques
Objective
Enhance prediction accuracy through pattern recognition. Model intricate relationships in meteorological data. Develop adaptable models for accurate predictions in various conditions.

Research Methodology

ANN Technique used

Software & Tools

Jupyter, Google Collab

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