基于GA-Bi-LSTM的盾构隧道下穿既有隧道沉降预测模型

doi:10.13722/j.cnki.jrme.2021.1187

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Abstract In order to provide support for the safety control of shield tunnel under-crossing the existing tunnel，genetic algorithm(GA) is used to optimize the structural parameters of Bi-directional Long Short-Term Memory(Bi-LSTM)，including the time series，units in hidden layer，hidden layers，Bi-LSTM layers，and dropout. And then，the existing tunnel settlement prediction model，named GA-Bi-LSTM，is constructed by comprehensively considering engineering geological parameters，spatial parameters，and shield construction parameters. Based on the settlement monitoring values and the corresponding construction parameters of the section project of Changsha Rail Transit Line 3 crossing Changsha Rail Transit Line 1 in parallel，the model is trained and tested. The results show that the mean absolute error(MAE)，root mean square error(RMSE) and sample regression value(R2) of the GA-Bi-LSTM model are 0.42，0.45 and 0.90 respectively，and the average relative error is only 10.78%. Compared with BP，SVM，LSTM and Bi-LSTM models，GA-Bi-LSTM model has better prediction accuracy，indicating that the model has better reliability and practicability，which can provide a new idea and method for the settlement prediction of the new tunnel under-crossing the existing tunnel.

Key words： tunnelling engineering shield tunnel neural network genetic algorithm prediction model settlement

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	Articles by authors
	ZHOU Zhong
	ZHANG Junjie
	DING Haohui
	LI Fan

Cite this article:

ZHOU Zhong,ZHANG Junjie,DING Haohui, et al. Settlement prediction model of shield tunnel under-crossing existing tunnel based on GA-Bi-LSTM[J]. , 2023, 42(1): 224-234.

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https://rockmech.whrsm.ac.cn/EN/10.13722/j.cnki.jrme.2021.1187 OR https://rockmech.whrsm.ac.cn/EN/Y2023/V42/I1/224

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