Literature Study on the Development of Neural Networks For Weather Forecasting

Amir, Fail
Utami, Ema
Hanafi, Hanafi

Jurnal Teknologi
Vol 17 No 1 (2024): Jurnal Teknologi

Weather prediction has always been crucial for individuals to make informed decisions and protect themselves from potential hazards. Achieving accurate weather forecasts has historically been a significant challenge. Modern weather forecasting has evolved to integrate sophisticated computer models, data from atmospheric balloons and satellites, and insights from local observations. These methods have resulted in fairly precise predictions. Most forecasting models depend on complex mathematical formulas, but Artificial Neural Networks (ANN) offer a dynamic alternative, adapting their structure based on incoming data. This research aimed to thoroughly evaluate the effectiveness of ANNs in weather prediction. It explored the advantages of ANNs over traditional models, reviewed a range of methodologies, and documented the latest advancements in the field. The ultimate goal was to consolidate research findings to highlight the strides made in enhancing weather forecasting through ANNs.