Analysis of repair costs of scholar buildings affected by earthquakes using data mining. case study: Earthquakes of 2017 in mexico

Graciela García-Rueda; Rosa M. Valdovinos; Jesús Valdés-González; Roberto Alejo; J. Leonardo González-Ruiz; José R. Marcial-Romero

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Analysis of repair costs of scholar buildings affected by earthquakes using data mining. case study: Earthquakes of 2017 in mexico

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2020) 12088 LNCS 45-56

DOI: 10.1007/978-3-030-49076-8_5

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Abstract

Earthquakes are events that cannot be predicted. However, when they occur, devastating consequences are shown in economic, social and structural areas, among others. In this paper, the mining of association rules is carried out in order to estimate the repair cost required by schools affected during the earthquakes of September 7th and 19th, of 2017 in Mexico. For that, we use the public data collected by the Mexican FONDEN.

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García-Rueda, G., Valdovinos, R. M., Valdés-González, J., Alejo, R., González-Ruiz, J. L., & Marcial-Romero, J. R. (2020). Analysis of repair costs of scholar buildings affected by earthquakes using data mining. case study: Earthquakes of 2017 in mexico. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12088 LNCS, pp. 45–56). Springer. https://doi.org/10.1007/978-3-030-49076-8_5

Analysis of repair costs of scholar buildings affected by earthquakes using data mining. case study: Earthquakes of 2017 in mexico

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