Classification via Nearest Prototype Classifier Utilizing Artificial Bee Colony on CUDA

  • Jan Janousešek
  • Petr Gajdoš
  • Michal Radecký
  • Václav Snášel
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 299)

Abstract

Artificial bee colony is a metaheuristic optimization algorithm based on the behaviour of honey bee swarm. These bees work largely independently of other bees, making the algorithm suitable for parallel implementation. Within this paper, we introduce the algorithm itself and its subsequent parallelization utilizing the CUDA platform. The runtime speedup is demonstrated on several commonly used test functions for optimization. The algorithm is subsequently applied to the problem of classifying real data.

Keywords

parallel algorithm artificial bee colony CUDA nearest prototype classifier classification 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jan Janousešek
    • 1
  • Petr Gajdoš
    • 1
  • Michal Radecký
    • 1
  • Václav Snášel
    • 1
  1. 1.Department of Computer Science, FEECSVŠB - Technical University of OstravaOstrava-PorubaCzech Republic

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