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Optimization of Artificial Neural Network: A Bat Algorithm-Based Approach

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Intelligent Systems Design and Applications (ISDA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 418))

Abstract

Artificial Neural Networks (ANNs) are dominant machine learning tools over the last two decades and are part of almost every computational intelligence task. ANNs have several parameters such as number of hidden layers, number of hidden neurons in each layer, variations in inter-connections between them, etc. Proposing an appropriate architecture for a particular problem while considering all parametric terms is an extensive and significant task. Metaheuristic approaches like particle swarm optimization, ant colony optimization, and cuckoo search algorithm have large contributions in the field of optimization. The main objective of this work is to design a new method that can help in the optimization of ANN architecture. This work takes advantage of the Bat algorithm and combines it with an ANN to find optimal architecture with minimal testing error. The proposed methodology had been tested on two different benchmark datasets and demonstrated results better than other similar methods.

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Authors and Affiliations

  1. Department of Computer Science, Jamia Millia Islamia, New Delhi, India

    Tarun Kumar Gupta & Khalid Raza

Authors
  1. Tarun Kumar Gupta
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  2. Khalid Raza
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Corresponding author

Correspondence to Khalid Raza .

Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  3. Institut für Wirtschaftsinformatik, Fachhochschule Nordwestschweiz, Olten, Switzerland

    Thomas Hanne

  4. Department of Computer Science and information Engineering, National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  5. Federal University of Bahia, Ondina, Brazil

    Tatiane Nogueira Rios

  6. Nantong University, Nantong Shi, Jiangsu, China

    Weiping Ding

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Gupta, T.K., Raza, K. (2022). Optimization of Artificial Neural Network: A Bat Algorithm-Based Approach. In: Abraham, A., Gandhi, N., Hanne, T., Hong, TP., Nogueira Rios, T., Ding, W. (eds) Intelligent Systems Design and Applications. ISDA 2021. Lecture Notes in Networks and Systems, vol 418. Springer, Cham. https://doi.org/10.1007/978-3-030-96308-8_26

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