Crow Search Optimization-Based Hybrid Meta-heuristic for Classification: A Novel Approach

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 710)

Abstract

This paper proposed a novel crow search optimization-based hybrid approach to solve classification problem of data mining. Being a recently developed population-based algorithm, crow search algorithm (CSA) has been strived the attention of all range researchers to solve wide range of complex engineering and optimization problems. In this paper, CSA is used with functional link neural network to solve classification problem. The results of the proposed method have been compared with other swarm-based approaches, and the experimental results reveal that the proposed method is superior to others.

Keywords

Crow search optimization FLANN Classification 

Notes

Acknowledgements

This work is supported by Technical Education Quality Improvement Programme, National Project Implementation Unit (A unit of MHRD, Govt. of India, for implementation of World Bank assisted projects in technical education), under the research project grant (VSSUT/TEQIP/37/2016).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer ApplicationVeer Surendra Sai University of TechnologyBurla, SambalpurIndia
  2. 2.Department of Computer Science and EngineeringSri Sivani College of EngineeringSrikakulamIndia

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