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Improved Levenberg–Marquardt backpropagation neural network by particle swarm and whale optimization algorithms to predict the deflection of RC beams

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Abstract

The aim of this study is to develop a novel computer-aided method for the prediction of the deflection of reinforced concrete beams (DRCB) under concentrated loads. To this end, in the present work, a Levenberg–Marquardt-based backpropagation novel neural network model, optimized by the whale optimization algorithm (WOA), called WOA-LMBPNN, has been developed. Specifically, a neural network, using the Levenberg–Marquardt backpropagation training algorithm with multiple hidden layers, was optimized by the WOA, aiming to obtain higher accuracy in predicting DRCB. For the training of the models, 120 experiments with the geometrical and mechanical properties of concrete beams were compiled using were used as the input parameters. Seven datasets with different number of input variables were investigated to evaluate the effect of the input variables on DRCB. For comparison purposes, another swarm optimization algorithm (i.e., particle swarm optimization—PSO) was also used to optimize the LMBPNN model (i.e., PSO-LMBPNN model). The results obtained by the PSO-LMBPNN and WOA-LMBPNN models are then compared based on the different datasets. Finally, the results revealed the effective role of the WOA, as well as the efficiency and robustness of the new hybrid WOA-LMBPNN model in predicting DRCB.

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Acknowledgements

Project supported by the Research Foundation of Education Bureau of Hunan Province(Grant No. 18A295).

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Authors and Affiliations

  1. Institute of Big Data and Internet Innovation and College of Computer and Information Engineering, Hunan University of Technology and Business, Changsha, 410205, China

    Jue Zhao

  2. Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam

    Hoang Nguyen

  3. Division of Computational Mathematics and Engineering, Institute for Computational Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Trung Nguyen-Thoi

  4. Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Trung Nguyen-Thoi

  5. Computational Mechanics Laboratory, School of Pedagogical and Technological Education, Heraklion, 14121, Athens, Greece

    Panagiotis G. Asteris

  6. School of Resources and Safety Engineering, Central South University, Changsha, 410083, Hunan, China

    Jian Zhou

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  1. Jue Zhao
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  2. Hoang Nguyen
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  3. Trung Nguyen-Thoi
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  4. Panagiotis G. Asteris
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Zhao, J., Nguyen, H., Nguyen-Thoi, T. et al. Improved Levenberg–Marquardt backpropagation neural network by particle swarm and whale optimization algorithms to predict the deflection of RC beams. Engineering with Computers 38 (Suppl 5), 3847–3869 (2022). https://doi.org/10.1007/s00366-020-01267-6

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