One of the most challenging tasks for tourism scientists is the prediction of potential overtourism situations in the tourist destinations. Until now, some efforts have been proposed for the purpose of establishing early warning systems. However, none of the attempts has tried to make use of a powerful prediction tool that is currently available: machine learning techniques. This article seeks to fill this gap in the existing literature by proposing the use of machine learning techniques in order to predict overtourism issues on a sample of Spanish tourist cities specialized in both, urban and sun and beach tourism products.

中文翻译：

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机器学习技术作为预测过度旅游的工具：西班牙的案例

对于旅游科学家来说，最具挑战性的任务之一是预测旅游目的地中潜在的过度旅游情况。迄今为止，已经提出了一些用于建立预警系统的努力。但是，没有任何尝试尝试利用当前可用的强大预测工具：机器学习技术。本文旨在通过建议使用机器学习技术来填补现有文献中的空白，以便在专门研究城市，阳光和海滩旅游产品的西班牙旅游城市样本中预测过度旅游问题。