MICAI 2016: Advances in Soft Computing pp 413-424 | Cite as

Data Mining in the Analysis of Ocean-Atmosphere Dynamics in Colombia’s Central Caribbean Ocean

  • Fran Ernesto Romero Alvarez
  • Oswaldo E. Vélez-Langs
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10062)

Abstract

This document presents a proposal for the development of an ocean-atmosphere dynamic predictive model for the central Caribbean region of Colombia. The proposal is based on temporary data mining techniques and includes the development of a software tool that complements the model. The software tool uses Weka API to implement several algorithms, such as data mining association rules, decision trees, classifiers, artificial neural networks and time series forecasting. The research results demonstrate the predictive power and advantages of using temporary Data Mining, rather than the conventional methods used in climate modeling.

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Notes

Acknowledgments

This research study has been financed by the OCEAN-ATMOSPHERE DYNAMICS IN THE CENTRAL CARRIBEAN REGION OF COLOMBIA. HISTORIC ASSESSMENT AND PREDICTION MODELS project, code 12201542 of internal call 11-2014 of the Jorge Tadeo Lozano University.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Fran Ernesto Romero Alvarez
    • 1
  • Oswaldo E. Vélez-Langs
    • 1
    • 2
  1. 1.Engineering DepartmentJorge Tadeo Lozano UniversityBogotá D.CColombia
  2. 2.Facultad de IngenieríaUniversidad de CórdobaMonteríaColombia

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