DE-GWO algorithm to optimize SVM inversion mechanical parameters of soft soil

RUAN Yong-fen; YU Dong-xiao; WU Long; TAN Gui-ping; LI Fei-peng; CHEN Bo

doi:10.11779/CJGE2021S1030

Volume 43 Issue S1

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Chinese Journal of Geotechnical Engineering > 2021 > 43(S1): 166-170. > DOI: 10.11779/CJGE2021S1030

RUAN Yong-fen, YU Dong-xiao, WU Long, TAN Gui-ping, LI Fei-peng, CHEN Bo. DE-GWO algorithm to optimize SVM inversion mechanical parameters of soft soil[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(S1): 166-170. DOI: 10.11779/CJGE2021S1030

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DE-GWO algorithm to optimize SVM inversion mechanical parameters of soft soil

1.
Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology, Kunming 650500, China
2.
Guangxi Hualan Geotechnical Engineering Co., Ltd., Nanning 530001, China
3.
China Railway 11th Bureau Group Urban Rail Engineering Co., Ltd, Wuhan 430074, China

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Received Date: December 19, 2020
Available Online: December 05, 2022

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Abstract

Abstract

The geotechnical mechanical parameters are the main basis for geotechnical engineering design and construction.In order to obtain the geotechnical parameter information that is more in line with the actual situation, a displacement back analysis method based on the support vector machines, faster and more accurate parameter determination method, is proposed.Based on the grey wolf algorithm, a swarm intelligence algorithm developed in nature bionics, and combined with the crossover mutation operation of the differential evolutionary algorithm, the grey wolf algorithm is evolved, and the hybrid grey wolf optimization algorithm is obtained, which is used to reverse the geotechnical mechanical parameters after optimization of the support vector machine parameters.Based on the subway tunnel project in Kunming, the Midas/GTS finite element is used to establish a three-dimensional simulation model to simulate the tunnel construction process.Based on the measured surface deformation of the top section of a tunnel, the support vector machine model optimized by the hybrid differential evolution grey wolf algorithm is used to invert the mechanical parameters of rock mass.The settlements calculated by the back analysis method and the traditional Peck formula method are compared with the meas surface ones.The results show that the calculated surface settlements based on the back analysis are basically consistent with the measured ones, and the calculated values by the other two methods differ greatly from the measured ones.The above analysis shows that the proposed method is reasonable and feasible, the reverse performance parameters are reasonable, and the calculated results are more accurate and in line with the reality.The proposed method can provide a new way for the acquisition and verification of the parameters of rock and soil mechanics.
- tunnel engineering,
- parameter inversion,
- support vector machine,
- differential evolution algorithm,
- grey wolf algorithm,
- displacement back analysis

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[1]	王文杰, 叶世伟. 人工智能原理与应用[M]. 北京: 人民邮电出版社, 2004. WANG Wen-jie, YE Shi-wei. Principles and applications of artificial intelligence[M]. Beijing: Posts&Telecom Press, 2004. (in Chinese)
[2]	CERNYCH M, SATAS A, BRAZAITIS M. Post-sauna recovery enhances brain neural network relaxation and improves cognitive economy in oddball tasks[J]. International Journal of Hyperthermia, 2018, 35(1): 375-382. doi: 10.1080/02656736.2018.1504992
[3]	李宁, 王李管, 贾明涛, 等. 改进遗传算法和支持向量机的岩体结构面聚类分析[J]. 岩土力学, 2014, 35(增刊2): 405-411. https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX2014S2058.htm LI Ning, WANG Li-guan, JIA Ming-tao, et al. Application of improved genetic algorithm and support vector machine to clustering analysis of rock mass structural plane[J]. Rock and Soil Mechanics, 2014, 35(S2): 405-411. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX2014S2058.htm
[4]	WANG Ding-wei, WANG Jun-wei, WANG Hong-feng. Intelligent OptimizationMethods[M]. Beijing: Higher Education Press, 2007.
[5]	漆祖芳, 姜清辉, 周创兵, 等. 基于v-SVR和MVPSO算法的边坡位移反分析方法及其应用[J]. 岩石力学与工程学报, 2013, 32(6): 1185-1196. doi: 10.3969/j.issn.1000-6915.2013.06.012 QI Zu-fang, JIANG Qinghui, ZHOU Chuang-bing, et al. A new slope displacement back analysis method based ON v-SVR and mvpso algorithm and its application[J]. Chinese Journal of Rock Mechanics and Engineering, 2013, 32(6): 1185-1196. (in Chinese) doi: 10.3969/j.issn.1000-6915.2013.06.012
[6]	Khatibinia Mohsen, Feizbakhsh Abdosattar, Ehsan Mohseni and Malek Mohammad Ranjbar. Modelingmechanical strength of self-compacting mortar containing nanoparticles using wavelet-based support vector machine[J]. Computers and Concrete, 2016, 18(6): 1065-1082.
[7]	张宝珍, 张尧, 林凌雪. 基于改进差分进化算法的估计等值法[J]. 华南理工大学学报(自然科学版), 2014, 42(4): 7-12, 18. doi: 10.3969/j.issn.1000-565X.2014.04.002 ZHANG Bao-zhen, ZHANG Yao, LIN Ling-xue. Estimation equivalence method based on modified differential evolution algorithm[J]. Journal of South China University of Technology(Natural Science Edition), 2014, 42(4): 7-12, 18. (in Chinese) doi: 10.3969/j.issn.1000-565X.2014.04.002
[8]	YANG X S, DEB S. Cuckoo search via lévy flights[C]//2009 World Congress on Nature&Biologically Inspired Computing(NaBIC). Coimbatore, 2009: 210-214
[9]	郭振洲, 刘然, 拱长青, 等. 基于灰狼算法的改进研究[J]. 计算机应用研究, 2017, 34(12): 3603-3606, 3610. doi: 10.3969/j.issn.1001-3695.2017.12.019 GUO Zhen-zhou, LIU Ran, GONG Chang-qing, et al. Studyonimprovementofgraywolfalgorithm[J]. Application Research of Computers, 2017, 34(12): 3603-3606, 3610. (in Chinese) doi: 10.3969/j.issn.1001-3695.2017.12.019
[10]	HEIDARI A A, PAHLAVANI P. An efficient modified grey wolf optimizer with Lévy flight for optimization tasks[J]. Applied Soft Computing, 2017, 60: 115-134. doi: 10.1016/j.asoc.2017.06.044
[11]	LU C, GAO L, YI J. Grey wolf optimizer with cellular topological structure[J]. Expert Systems With Applications, 2018, 107: 89-114. doi: 10.1016/j.eswa.2018.04.012
[12]	方开泰, 马长兴. 正交与均匀试验设计[M]. 北京: 科学出版社, 2001. FANG Kai-tai, MA Chang-xing. Orthogonal and uniform experiment design[M]. Beijing: Science Press, 2001. (in Chinese)
[13]	梅松华, 盛谦, 冯夏庭. 均匀设计在岩土工程中的应用[J]. 岩石力学与工程学报, 2004, 23(16): 2694-2697. doi: 10.3321/j.issn:1000-6915.2004.16.007 MEI Song-hua, SHENG Qian, FENG Xia-ting. Geotechnical engineering[J]. Chinese Journal of Rock Mechanics and Engineering, 2004, 23(16): 2694-2697. (in Chinese) doi: 10.3321/j.issn:1000-6915.2004.16.007
[14]	韩煊, 李宁, Standing J. R.. Peck公式在中国隧道施工地面变形预测中的适用性分析[J]. 岩土力学, 2007, 28(1): 23-28, 35. https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX200701005.htm HAN Xuan, LI Ning, STANDING J R. An adaptability study of Gaussian equation applied to predicting ground settlements induced by tunneling in China[J]. Rock and Soil Mechanics, 2007, 28(1): 23-28, 35. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX200701005.htm