Grouting reinforcement strategy for tunnel sand layer based on BP neural network

[1] Uliasz-Misiak, B., Przybycin, A. (2016). Present and future status of the underground space use in Poland. Environmental earth sciences, 75-22. Search in Google Scholar

[2] Wang, S., Zhang, X., Cao, J., et al.(2017). Computing urban traffic congestions by incorporating sparse GPS probe data and social media data. Acm Transactions on Information Systems, 35(4):40. Search in Google Scholar

[3] Yin, R., Song, X. (2022). Mitigation strategy of cascading failures in urban traffic congestion based on complex networks. International Journal of Modern Physics C. Search in Google Scholar

[4] Feng, X. (2016). Improve urban passenger transport management by rationally forecasting traffic congestion probability. International Journal of Production Research, 54(12), 3465-3474. Search in Google Scholar

[5] Cao, Z., Jiang, S., Jie, Z., et al. (2017). A Unified Framework for Vehicle Rerouting and Traffic Light Control to Reduce Traffic Congestion. IEEE Transactions on Intelligent Transportation Systems, 18(7), 1958-1973. Search in Google Scholar

[6] Li, Z., Pan, L., Xu, C., et al. (2017). Reinforcement Learning-Based Variable Speed Limit Control Strategy to Reduce Traffic Congestion at Freeway Recurrent Bottlenecks. IEEE Transactions on Intelligent Transportation Systems, 11, 1-14. Search in Google Scholar

[7] Hou, W., Yang, L., Deng, D., et al. (2016). Assessing quality of urban underground spaces by coupling 3D geological models: The case study of Foshan city, South China. Computers & Geosciences, 89(Apr.), 1-11. Search in Google Scholar

[8] Ganesha, A. V., Prakash, N., Prasanna, K. L. (2017). Geological investigation on the causes of collapse of irrigation tunnel. -a case study from Hulikere, Mandya district, Karnataka. Engineering Geology, XLII(1-2), 265-274. Search in Google Scholar

[9] Wang, D. F., Xu, H. D., Wang, L., et al. (2020). Statistical analyses of the effect of a drainage tunnel on landslide hydrogeological characteristics. Hydrological Processes, 34(1). Search in Google Scholar

[10] Bandini, A., Berry, P., Boldini, D. (2015). Tunnelling-induced landslides: The Val di Sambro tunnel case study. Engineering Geology, 196, 71-87. Search in Google Scholar

[11] He, X., Zhou, X., Xu, Y., et al. (2020). Study on the Influence of Nonlinear Seepage and Grouting Reinforcement on Surrounding Rock in Subsea Tunnel. Journal of Coastal Research, 111(sp1). Search in Google Scholar

[12] Baosong, Shu, Biao. (2015). Study of ground collapse induced by large-diameter horizontal directional drilling in a sand layer using numerical modeling. Canadian Geotechnical Journal. Search in Google Scholar

[13] He, X., Zhou, X., Xu, Y., et al. (2020). Study on the Influence of Nonlinear Seepage and Grouting Reinforcement on Surrounding Rock in Subsea Tunnel. Journal of Coastal Research, 111(sp1). Search in Google Scholar

[14] He, X., Zhou, X., Xu, Y., et al. (2020). Study on the Influence of Nonlinear Seepage and Grouting Reinforcement on Surrounding Rock in Subsea Tunnel. Journal of Coastal Research, 111(sp1). Search in Google Scholar

[15] Alagna, V., Bagarello, V., Prima, S. D., et al. (2016). Testing infiltration run effects on the estimated water transmission properties of a sandy-loam soil. Geoderma, 267, 24-33. Search in Google Scholar

[16] Fugang, X. U., Gao, J., Wang, J., et al. (2015). Formation mechanism and its countermeasures for cracks in rock- anchored beam during the construction process of underground caverns at the Houziyan Hydropower Station. Journal of Hydraulic Engineering. Search in Google Scholar

[17] Butchibabu, B., Khan, P. K., Jha, P. C. (2018). Foundation evaluation of underground metro rail station using geophysical and geotechnical investigations. Engineering Geology, 248. Search in Google Scholar

[18] Hu, Q., Gu, Y., Zeng, J., et al. (2019). Microwave irradiation reinforcement of weak muddy intercalation in slope[J]. Applied Clay Science, 183, 105324. Search in Google Scholar

[19] Zhang, M. (2017). Application of BP neural network in acoustic wave measurement system. Modern Physics Letters B, 31(19-21), 1740052. Search in Google Scholar

[20] Wang, W., Tang, R., Li, C., et al. (2018). A BP neural network model optimized by Mind Evolutionary Algorithm for predicting the ocean wave heights. Ocean Engineering, 162(aug.15), 98-107. Search in Google Scholar

[21] Wang, S., Wu, T. H., Shao, T., et al. (2019). Integrated model of BP neural network and CNN algorithm for automatic wear debris classification. Wear, 426-427, 1761-1770. Search in Google Scholar

[22] Zhao, H., Shi, S., Jiang, H., et al. (2017). Calibration of AOTF-based 3D measurement system using multiplane model based on phase fringe and BP neural network. Optics Express, 25(9), 10413. Search in Google Scholar

[23] Liu, Y. K., Xie, F., Xie, C. L., et al. (2015). Prediction of time series of NPP operating parameters using dynamic model based on BP neural network. Annals of Nuclear Energy, 85, 566-575. Search in Google Scholar

[24] Han, X. H., Xiong, X., Duan, F. (2015). A new method for image segmentation based on BP neural network and gravitational search algorithm enhanced by cat chaotic mapping. Applied Intelligence, 43(4), 855-873. Search in Google Scholar

[25] Peng, K. X., Yang, J. B., Tuo, X. G., et al. (2016). Research on PGNAA adaptive analysis method with BP neural network. Modern Physics Letters B, 30(32n33), 1650386. Search in Google Scholar

[26] Kovaevi, M. S., Bai, M., Gavin, K. (2020). Application of Neural Networks for the Reliability Design of a Tunnel in Karst Rock Mass. Canadian Geotechnical Journal, 1. Search in Google Scholar