论文标题
通过机器学习预测龙卷风的日子
Predicting Tornadoes days ahead with Machine Learning
论文作者
论文摘要
开发预测灾难性自然现象的方法比以往任何时候都重要，龙卷风是自然界中最危险的。由于天气的不可预测性，抵消它们并不是一件容易的事，如今，它主要由专家气象学家（解释气象模型）进行。在本文中，我们提出了一个用于早期检测龙卷风的系统，在现实世界中验证了其有效性，并利用已经在全球广泛普遍存在的气象数据收集系统。我们的系统能够预测龙卷风，最大概率为84％，直到活动发生在事件发生前五天，这是一个超过5000次龙卷风和非龙卷风事件的新型数据集。数据集和重现我们的结果的代码可在以下网址获得：https：//tinyurl.com/3brsfwpk
Developing methods to predict disastrous natural phenomena is more important than ever, and tornadoes are among the most dangerous ones in nature. Due to the unpredictability of the weather, counteracting them is not an easy task and today it is mainly carried out by expert meteorologists, who interpret meteorological models. In this paper we propose a system for the early detection of a tornado, validating its effectiveness in a real-world context and exploiting meteorological data collection systems that are already widespread throughout the world. Our system was able to predict tornadoes with a maximum probability of 84% up to five days before the event on a novel dataset of more than 5000 tornadic and non-tornadic events. The dataset and the code to reproduce our results are available at: https://tinyurl.com/3brsfwpk
