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Harmony-driven technique for solving optimization and engineering problems

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Abstract

Optimization techniques play a crucial role in improving the performance of machine learning applications. However, traditional techniques may not be suitable for addressing complex problems that involve numerous parameters requiring adaptation. This paper presents a novel variant of the gradient-based optimizer (GBO) and investigates the effectiveness of integrating the harmony search (HS) algorithm to enhance the GBO algorithm. The HS algorithm offers several advantages, including fast convergence and fewer adjustable parameters. The proposed method, called GBOHS, is evaluated through three experiments. The first experiment focuses on solving global optimization problems, while the second experiment assesses its ability to select the most relevant features using sixteen benchmark feature selection datasets. The final experiment applies the GBOHS method to solve five real engineering problems. The results are compared against those of well-known optimization algorithms using various performance measures, including fitness function value and classification accuracy. The findings demonstrate that the proposed GBOHS method achieves high accuracy and consistently outperforms the compared methods across all the experiments, demonstrating its promising effectiveness.

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Data availability

The data that support the findings of this study are available on [29] and [34].

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Acknowledgements

The authors are thankful to the Deanship of Graduate Studies and Scientific Research at University of Bisha for supporting this work through the Fast-Track Research Support Program.

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The author declares that no funds, grants, or other support were received during the preparation of this manuscript.​

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Authors and Affiliations

  1. Department of Information System and Cybersecurity, College of Computing and Information Technology, University of Bisha, P.O Box 551, Bisha, Saudi Arabia

    Ahmed A. Ewees

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  1. Ahmed A. Ewees
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A. Ewees was involved in conceptualization, methodology, investigation, data curation, writing—original draft, and writing—reviewing and editing.

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Correspondence to Ahmed A. Ewees.

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Ewees, A.A. Harmony-driven technique for solving optimization and engineering problems. J Supercomput 80, 17980–18008 (2024). https://doi.org/10.1007/s11227-024-06100-1

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