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Coevolutionary Recurrent Neural Networks for Prediction of Rapid Intensification in Wind Intensity of Tropical Cyclones in the South Pacific Region

机译:基于协进化神经网络的南太平洋地区热带气旋风强度快速增强预测

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Rapid intensification in tropical cyclones occur where there is dramatic change in wind-intensity over a short period of time. Recurrent neural networks trained using cooperative coevolution have shown very promising performance for time series prediction problems. In this paper, they are used for prediction of rapid intensification in tropical cyclones in the South Pacific region. An analysis of the tropical cyclones and the occurrences of rapid intensification cases is assessed and then data is gathered for recurrent neural network for rapid intensification predication. The results are promising that motivate the implementation of the system in future using cloud computing infrastructure linked with mobile applications to create awareness.
机译:热带气旋会在短时间内风速发生剧烈变化时迅速加剧。使用协作协同进化训练的递归神经网络对于时间序列预测问题已显示出非常有前途的性能。在本文中,它们被用于预测南太平洋地区热带气旋的快速集约化。评估了热带气旋的分析和快速强化病例的发生,然后收集了用于递归神经网络的数据,以进行快速强化预测。研究结果令人鼓舞,它可以通过与移动应用程序链接的云计算基础架构来激发人们的意识,从而激励该系统的实施。

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