• Volume: 1
• Issue:03
• Date: 26-03-2024

Title : Review of a Rainfall Forecasting System Using AI Techniques

Abstract: Rainfall forecasting is crucial for various applications, including agriculture, water resource management, and disaster preparedness. This review paper provides a comprehensive examination of the advancements in rainfall forecasting systems utilizing artificial intelligence (AI) techniques. The review explores a range of AI methodologies applied to enhance the accuracy and reliability of rainfall predictions, including machine learning algorithms, neural networks, and hybrid models. Key areas covered include the evolution of forecasting models, the integration of AI with traditional meteorological approaches, and the impact of data sources such as satellite imagery and weather stations. The paper also discusses the benefits and limitations of different AI techniques in rainfall forecasting, highlighting their effectiveness in different geographical regions and climatic conditions. By analyzing recent developments and trends, this review aims to provide valuable insights into the future directions of AIdriven rainfall forecasting systems, emphasizing their potential to improve predictive accuracy and support decision-making processes in climate-sensitive sectors

Key Words: Rainfall Forecasting, Artificial Intelligence, Machine Learning, Neural Networks, Predictive Models, Hybrid Forecasting Models, Meteorological Data

Area: Engineering

• Approved ISSN: ----
• Paper Id: IJREISTU11
• Page No: 17-21

• Author: Neeru Kumari

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• Co- Author: Jeetendra Singh Yadav