智慧城市空气质量预测

Kristina Matović, Nataša Vlahović
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引用次数: 1

摘要

技术和工业进步是造成环境污染的主要问题和原因之一。工业、发电厂、交通、工厂是大城市的主要污染物。另一方面,同样的技术进步也可以用来减少这种不良影响。其中一种方法是智能城市传感器网络,其应用程序可以预测未来几天的空气质量,并在即将到来的严重污染情况下向人们发出警告。本文中的预测任务是通过使用最先进的算法(如CatBoost)进行的,并带有有助于提高模型质量的附加功能。研究了三种模型,常规的CatBoost,附加变量的CatBoost,以及用另一个模型增强CatBoost模型的新方法。对所有模型进行了比较,通过新方法boost CatBoost获得了最佳性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Air Quality Prediction in Smart City
Technological and industrial advancement is one of the main problems and causes of environmental pollution. Industry, power plants, traffic, factories are the main pollutants in big cities. On the other hand, the same technological advancement can also be used to decrease this bad influence. One of the ways is a smart city sensor network with applications that can predict air quality for the next few days and warn the population in the case of the upcoming severe pollution. The prediction task in this paper is conducted by using state-of-the-art algorithms such as CatBoost, with additional features that help improve the quality of the model. Three models are examined, regular CatBoost, CatBoost with additional variable, and the new approach where CatBoost model is boosted with another model. All the models are compared, while the best performance is achieved via the new approach Boosted CatBoost.
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