首页|Research on Machine Learning Reported by Researchers at Korea Institute of Ocean Science and Technology (Predicting rapid in- tensification of tropical cyclones in the western North Pacific: a machine learning and net energy gain rate approach)
Research on Machine Learning Reported by Researchers at Korea Institute of Ocean Science and Technology (Predicting rapid in- tensification of tropical cyclones in the western North Pacific: a machine learning and net energy gain rate approach)
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2024 FEB 02 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on artificial intelligence. According to news reporting from Busan, South Korea, by NewsRx journalists, research stated, “In this study, a machine learning (ML)- based Tropical Cyclones (TCs) Rapid Intensification (RI) prediction model has been developed by using the Net Energy Gain Rate Index (NGR). This index realistically captures the energy exchanges between the ocean and the atmosphere during the intensification of TCs.” Our news correspondents obtained a quote from the research from Korea Institute of Ocean Science and Technology: “It does so by incorporating the thermal conditions of the upper ocean and using an accurate parameterization for sea surface roughness. To evaluate the effectiveness of NGR in enhancing prediction accuracy, five distinct ML algorithms were utilized: Decision Tree, Logistic Regression, Support Vector Machine, K-Nearest Neighbors, and Feed-forward Neural Network. Two sets of experiments were performed for each algorithm. The first set used only traditional predictors, while the second set incorporated NGR. The outcomes revealed that models trained with the inclusion of NGR exhibited superior performance compared to those that only used traditional predictors. Additionally, an ensemble model was developed by utilizing a hard-voting method, combining the predictions of all five individual algorithms.”
Korea Institute of Ocean Science and TechnologyBusanSouth KoreaAsiaCyborgsEmerging TechnologiesMachine Learning
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