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Effectiveness of Swarm-Based Metaheuristic Algorithm in Data Classification Using Pi-Sigma Higher Order Neural Network

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Progress in Advanced Computing and Intelligent Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1199))

Abstract

In this paper, Salp Swarm Algorithm (SSA) is employed in training the Higher Order Neural Network (HONN) for data classification task. In machine learning approach, to train artificial neural network is considered a difficult task which gains the attention of researchers recently. The difficulty of Artificial Neural Networks (ANNs) arises due to its nonlinearity nature and unknown set of initial parameters. Traditional training algorithms exhibit poor performance in terms of local optima avoidance and convergence rate, for which metaheuristic based optimization emerges as a suitable alternative. The performance of the proposed SSA-based HONN method has been verified by considering various classification measures over benchmark datasets chosen from UCI repository and the outcome obtained by the said method is compared with the state-of-art evolutionary algorithms. From the outcome reported, the proposed method outperforms over the recent algorithms which confirm its supremacy in terms of better exploration and exploitation capability.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Burla, 768018, Odisha, India

    Nibedan Panda & Santosh Kumar Majhi

  2. Department of Information Technology, Aditya Institute of Technology and Management, Tekkali, 532201, Andra Pradesh, India

    Nibedan Panda

Authors
  1. Nibedan Panda
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  2. Santosh Kumar Majhi
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Corresponding author

Correspondence to Nibedan Panda .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Rama Devi Women's University, Bhubaneswar, India

    Chhabi Rani Panigrahi

  2. Department of Computer Science, Rama Devi Women's University, Bhubaneswar, India

    Bibudhendu Pati

  3. Department of Computer Science, University of California, Davis, CA, USA

    Prasant Mohapatra

  4. Cloud Computing and Distributed Systems (CLOUDS) Lab, School of Computing and Information Systems, The University of Melbourne, Melbourne, VIC, Australia

    Rajkumar Buyya

  5. Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan

    Kuan-Ching Li

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Panda, N., Majhi, S.K. (2021). Effectiveness of Swarm-Based Metaheuristic Algorithm in Data Classification Using Pi-Sigma Higher Order Neural Network. In: Panigrahi, C.R., Pati, B., Mohapatra, P., Buyya, R., Li, KC. (eds) Progress in Advanced Computing and Intelligent Engineering. Advances in Intelligent Systems and Computing, vol 1199. Springer, Singapore. https://doi.org/10.1007/978-981-15-6353-9_8

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  • DOI: https://doi.org/10.1007/978-981-15-6353-9_8

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-6352-2

  • Online ISBN: 978-981-15-6353-9

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