RETRACTED ARTICLE: A new prediction method for surface settlement of deep foundation pit in pelagic division based on Elman-Markov model

Zhan, Yubao; Zhang, Jun; Liu, Qihua; Zheng, Pengfei

doi:10.1007/s12517-021-07603-4

Cited by 5 publications

(1 citation statement)

References 10 publications

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“…Zhan et al proposed an Elman network-based surface settlement prediction method to predict the surface settlement of deep foundation pits in oceanic lots and then correct the predicted values by the Markov chain model, thus further improving the accurate prediction of deep foundation pits in deep marine areas. ey also found that this method has a good denoising effect and is practical through practice [6]. Liu et al constructed a tunnel settlement prediction model represented by Zhengzhou based on the currently available monitoring data.…”

Section: Introductionmentioning

confidence: 98%

Research on the Settlement Prediction Model of Foundation Pit Based on the Improved PSO-SVM Model

Song

Liu

Jiang

et al. 2022

Scientific Programming

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This paper presents a settlement prediction method based on PSO optimized SVM for improving the accuracy of foundation pit settlement prediction. Firstly, the method uses the SA algorithm to improve the traditional PSO algorithm, and thus, the overall optimization-seeking ability of the PSO algorithm is improved. Secondly, the improved PSO algorithm is used to train the SVM algorithm. Finally, the optimal SVM model is obtained, and the trained model is used in foundation pit settlement prediction. The results suggest that the settling results obtained from the optimized model are closer to the actual values and also more advantageous in indicators such as RMSE. The fitting value R2 = 0.9641, which is greater, indicates a better fitting effect. Thus, it is indicated that the improvement method is feasible.

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Section: Introductionmentioning

confidence: 98%