International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 184 - Number 16 |
Year of Publication: 2022 |
Authors: F.S. Sourjah, W.P.J. Pemarathne |
10.5120/ijca2022922162 |
F.S. Sourjah, W.P.J. Pemarathne . Heat Wave Prediction using Machine Learning Techniques: A Review. International Journal of Computer Applications. 184, 16 ( Jun 2022), 33-40. DOI=10.5120/ijca2022922162
Heat waves have become one of the major calamities in the present world because of global warming and the rise in temperature. Exceptional temperatures that are recorded over a period can be known as extreme heat events or heat waves. Even though heat waves are less exciting than other disasters like floods, tornados and earthquakes, they are an equivalent hazard to the existence of life on earth. It is critical to forecast heatwaves throughout the year and take the necessary precautions to avoid losses. Due to the advancement in machine learning (ML) techniques, ML can become handy in predicting heat waves. Our main objective is to study different existing ML algorithms that can be used to predict extreme heat events. The main approach to this study is to review the existing studies of machine learning techniques like the use of regression algorithm, K-Nearest Neighbour algorithm, Deep Learning algorithms and other significant ML algorithms that are being used to predict heatwaves and heatwave-related predictions. This research study will help to compare and contrast different ML algorithms to help this research derive the best ML model that can be developed for future heat wave predictions.