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Prediction of Ultimate Bearing Capacity of Soil–Cement Mixed Pile Composite Foundation Using SA-IRMO-BPNN Model

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  • Lin Xi

    (School of Civil Engineering, Central South University, Central South University Railway Campus, No. 22, Shaoshan South Rd., Changsha 410075, China)

  • Liangxing Jin

    (School of Civil Engineering, Central South University, Central South University Railway Campus, No. 22, Shaoshan South Rd., Changsha 410075, China)

  • Yujie Ji

    (School of Civil Engineering, Central South University, Central South University Railway Campus, No. 22, Shaoshan South Rd., Changsha 410075, China)

  • Pingting Liu

    (School of Civil Engineering, Central South University, Central South University Railway Campus, No. 22, Shaoshan South Rd., Changsha 410075, China)

  • Junjie Wei

    (School of Civil Engineering, Central South University, Central South University Railway Campus, No. 22, Shaoshan South Rd., Changsha 410075, China)

Abstract

The prediction of the ultimate bearing capacity (UBC) of composite foundations represents a critical application of test monitoring data within the field of intelligent geotechnical engineering. This paper introduces an effective combinational prediction algorithm, namely SA-IRMO-BP. By integrating the Improved Radial Movement Optimization (IRMO) algorithm with the simulated annealing (SA) algorithm, we develop a meta-heuristic optimization algorithm (SA-IRMO) to optimize the built-in weights and thresholds of backpropagation neural networks (BPNN). Leveraging this integrated prediction algorithm, we forecast the UBC of soil–cement mixed (SCM) pile composite foundations, yielding the following performance metrics: RMSE = 3.4626, MAE = 2.2712, R = 0.9978, VAF = 99.4339. These metrics substantiate the superior predictive performance of the proposed model. Furthermore, we utilize two distinct datasets to validate the generalizability of the prediction model presented herein, which carries significant implications for the safety and stability of civil engineering projects.

Suggested Citation

  • Lin Xi & Liangxing Jin & Yujie Ji & Pingting Liu & Junjie Wei, 2024. "Prediction of Ultimate Bearing Capacity of Soil–Cement Mixed Pile Composite Foundation Using SA-IRMO-BPNN Model," Mathematics, MDPI, vol. 12(11), pages 1-24, May.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:11:p:1701-:d:1405496
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    References listed on IDEAS

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    1. Robert Serfling & Satyaki Mazumder, 2013. "Computationally easy outlier detection via projection pursuit with finitely many directions," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(2), pages 447-461, June.
    2. Patrick Ten Eyck & Joseph E. Cavanaugh, 2018. "Model selection criteria based on cross-validatory concordance statistics," Computational Statistics, Springer, vol. 33(2), pages 595-621, June.
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