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

Lin Xi, Liangxing Jin (), Yujie Ji, Pingting Liu and Junjie Wei
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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

Mathematics, 2024, vol. 12, issue 11, 1-24

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.

Keywords: composite foundation; soil–cement mixing pile; ultimate bearing capacity; BP neural network; SA-IRMO-BPNN model; meta-heuristic optimization algorithm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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