Conference Proceedings
The International Conference on Emerging Technologies in Electronics, Computing and Communication 2022
(ICETECC`22)
Regional Heatwave Prediction Using deep learning based Recurrent Neural Network
Saqiba Juna1*; Sanam Narejo1; Muhammad Moazzam Jawaid1;| 1Department of Computer System MUET |
ABSTRACT
The increased frequency and severity of heatwaves are a result of global warming's increasing temperatures. The performance of various reliable prediction models has decreased as a result of changes in the world environment. LSTM neural networks, among other deep learning-based recurrent neural network algorithms, are used to develop a reliable model for the prediction of heatwave maximum temperature. In this research, We have developed a percentile-based threshold over the predicted maximum temperature to forecast heatwaves using LSTM based predictive model. The LSTM algorithm was applied in this study to determine the approximate maximum temperature for a severe heatwave.