Conglomerates of Latin American countries and public policies for the sustainable development of the electric power generation sector

Leadina Sanchez, Carmen Vásquez, Amelec Viloria, Cmeza-Estrada

    Producción científica: Capítulo del libro/informe/acta de congresoContribución de conferenciarevisión exhaustiva

    17 Citas (Scopus)

    Resumen

    Due to the effects of greenhouse gases, countries have implemented policies to slow down their emissions. Latin America stands out as one of the regions that have seen these effects accentuated, among them, the vulnerability of its electrical systems to periods of drought. The objective of this paper is to classify the group of these countries that contribute more or less to the emissions of these gases, in relation to their generation of electric power. The data used to carry out this classification are those reported by databases such as: Latin American Energy Organization (OLADE, by its initials in Spanish) and the World Bank, for the period from 2006 to 2013. The big data are analyzed using data mining techniques: Grouping and Association. The results show that they were organized in three (3) clusters. In the efficient one is Brazil, with an average of 289.66 tons/GWh emissions. In the clusters, considered inefficient, they have an average emissions of 462.15 and 1137.10 ton/GWh.

    Idioma originalInglés
    Título de la publicación alojadaData Mining and Big Data - 3rd International Conference, DMBD 2018, Proceedings
    EditoresYuhui Shi, Qirong Tang, Ying Tan
    EditorialSpringer Verlag
    Páginas759-766
    Número de páginas8
    ISBN (versión impresa)9783319938028
    DOI
    EstadoPublicada - 2018
    Evento3rd International Conference on Data Mining and Big Data, DMBD 2018 held in conjunction with the 9th International Conference on Swarm Intelligence, ICSI 2018 - Shanghai, China
    Duración: 17 jun. 201822 jun. 2018

    Serie de la publicación

    NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volumen10943 LNCS
    ISSN (versión impresa)0302-9743
    ISSN (versión digital)1611-3349

    Conferencia

    Conferencia3rd International Conference on Data Mining and Big Data, DMBD 2018 held in conjunction with the 9th International Conference on Swarm Intelligence, ICSI 2018
    País/TerritorioChina
    CiudadShanghai
    Período17/06/1822/06/18

    Nota bibliográfica

    Publisher Copyright:
    © Springer International Publishing AG, part of Springer Nature 2018.

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