Accident localization at the district heating network of Kaunas Region using machine learning

Autor: Bukauskas, M., Mantas Lukoševičius
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Scopus-Elsevier
Popis: Machine learning is constantly gaining popularity in real life applications. And one of them is prediction of various real-life events that depend on a huge number of factors that are hard to evaluate. In this article we describe the process of applying XGBoost — one of supervised machine learning methods — to help in prediction and localization of accidents in the district heating network of Kaunas region. We also investigate the importance of the different factors for these events.
Databáze: OpenAIRE