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A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting

  • Ricardo L. Talavera-Llames
  • Rubén Pérez-Chacón
  • María Martínez-Ballesteros
  • Alicia Troncoso
  • Francisco Martínez-ÁlvarezEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9648)

Abstract

A forecasting algorithm for big data time series is presented in this work. A nearest neighbours-based strategy is adopted as the main core of the algorithm. A detailed explanation on how to adapt and implement the algorithm to handle big data is provided. Although some parts remain iterative, and consequently requires an enhanced implementation, execution times are considered as satisfactory. The performance of the proposed approach has been tested on real-world data related to electricity consumption from a public Spanish university, by using a Spark cluster.

Keywords

Big data Nearest neighbours Time series Forecasting 

Notes

Acknowledgments

The authors would like to thank the Spanish Ministry of Economy and Competitiveness, Junta de Andalucía, Fundación Pública Andaluza Centro de Estudios Andaluces and Universidad Pablo de Olavide for the support under projects TIN2014-55894-C2-R, P12-TIC-1728, PRY153/14 and APPB813097, respectively.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Ricardo L. Talavera-Llames
    • 1
  • Rubén Pérez-Chacón
    • 1
  • María Martínez-Ballesteros
    • 2
  • Alicia Troncoso
    • 1
  • Francisco Martínez-Álvarez
    • 1
    Email author
  1. 1.Division of Computer ScienceUniversidad Pablo de OlavideSevilleSpain
  2. 2.Department of Computer ScienceUniversity of SevilleSevilleSpain

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