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Exploring the Potential of Cuckoo Search Algorithm for Classification and Function Approximation

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Modeling and Simulation in Engineering, Economics and Management (MS 2016)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 254))

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Abstract

In this paper we conduct some experiments with one of the most promising nature-inspired metaheuristic algorithm for optimization, known as Cuckoo Search (CS). It is essentially based on the cuckoo breeding behavior, which consists of dumping eggs in the nests of host birds and letting these host birds raise their chicks. The aim of this paper is to explore the performance of CS metaheuristic when it is used to evolve Neural Network for classification or function approximation.

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References

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Author information

Authors and Affiliations

  1. Department of Statistics and Informatics, University of Craiova, Craiova, Romania

    Vasile Georgescu

Authors
  1. Vasile Georgescu
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Correspondence to Vasile Georgescu .

Editor information

Editors and Affiliations

  1. Dept of Accounting & Finance, University of Zaragoza, Zaragoza, Spain

    Raúl León

  2. University Jaume I, Castellón de la Plana, Spain

    María Jesús Muñoz-Torres

  3. Dept of Accounting & Finance, University of Zaragoza, Zaragoza, Spain

    Jose M. Moneva

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© 2016 Springer International Publishing Switzerland

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Georgescu, V. (2016). Exploring the Potential of Cuckoo Search Algorithm for Classification and Function Approximation. In: León, R., Muñoz-Torres, M., Moneva, J. (eds) Modeling and Simulation in Engineering, Economics and Management. MS 2016. Lecture Notes in Business Information Processing, vol 254. Springer, Cham. https://doi.org/10.1007/978-3-319-40506-3_19

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