Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Entire DC Network
A Data Science Approach To Assess Resilience And Complexity In The European Transmission Power Grid, Mar Fernandez, Marti Rosas-Casals, Gibert Karina
A Data Science Approach To Assess Resilience And Complexity In The European Transmission Power Grid, Mar Fernandez, Marti Rosas-Casals, Gibert Karina
International Congress on Environmental Modelling and Software
In this paper, we aim at assessing the complexity and resilience of the European Transmission Power Grid (ETPG) following a data science approach. We consider open data related to energy policies and infrastructural and economic variables, together with ETPG reliability data (i.e., major failures and blackout data) of most European countries, considering data from a period of 14 years’ (2002 – 2014). A Data Science approach is used to understand spatio-temporal patterns of failures and blackouts of the ETPG along the different countries and periods. A combination of clustering methods with post-processing interpretation techniques and complex networks analysis is applied …
Understanding The Impact Of Climate And Traffic In Air Quality: The Impact Of Preprocessing In Data Science, Gibert Karina, Miquel Sànchez Marrè, Gerardo Ezequiel Martin, Nora Solé-Corcoll, Laura Vilardell-Magre
Understanding The Impact Of Climate And Traffic In Air Quality: The Impact Of Preprocessing In Data Science, Gibert Karina, Miquel Sànchez Marrè, Gerardo Ezequiel Martin, Nora Solé-Corcoll, Laura Vilardell-Magre
International Congress on Environmental Modelling and Software
In the context of smart cities, more and more real time information is available to a better management. The paper shows how a detailed preprocessing helps to a better modelling of air quality based on combining several open data sources like climate, traffic and pollution monitoring in the city of Barcelona. Traffic information can be viewed in GIS and associated with pollutants and climate information. The work shows how the preprocessing of different kinds of data can be encompassed into a global Data Science process usefull to support environmental plans in the city