Stability evaluation model for loess deposits based on PCA-PNN |
Li, Guangkun
(Geotechnical and Structural Engineering Research Center, Shandong University)
Su, Maoxin (Geotechnical and Structural Engineering Research Center, Shandong University) Xue, Yiguo (Geotechnical and Structural Engineering Research Center, Shandong University) Song, Qian (Geotechnical and Structural Engineering Research Center, Shandong University) Qiu, Daohong (Geotechnical and Structural Engineering Research Center, Shandong University) Fu, Kang (Geotechnical and Structural Engineering Research Center, Shandong University) Wang, Peng (Geotechnical and Structural Engineering Research Center, Shandong University) |
1 | Graziani, A. and Boldini, D. (2012), "Remarks on axisymmetric modeling of deep tunnels in argillaceous formations. I: Plastic clays", Tunn. Undergr. Sp. Tech., 28, 70-79. https://doi.org/10.1016/j.tust.2011.09.006. DOI |
2 | Ziegel, E.R. (2005), "Discovering knowledge in data/next generation of data-mining applications", Technometrics, 47(4), 528-529. |
3 | Zhou, B.H., Xue, Y.G., Li, S., Qiu, D., Tao, Y., Zhang, K. and Xia, T. (2020), "Probabilistic analysis of tunnel collapse: Bayesian method for detecting change points", Geomech. Eng., 22(4), 291-303. https://doi.org/10.12989/gae.2020.22.4.291. DOI |
4 | Ren, X.C., Lai, Y.M., Zhang, F.Y. and Hu, K. (2015), "Test method for determination of optimum moisture content of soil and maximum dry density", Ksce J. Civil Eng., 19, 2061-2066. https://doi.org/10.1007/s12205-015-0163-0. DOI |
5 | Rogers, CDF., Dijkstra, T.A. and Smalley, I.J. (1994), "Particle packing from an earth-science viewpoint", Earth-Sci. Reviews, 36, 59-82. https://doi.org/10.1016/0012-8252(94)90008-6. DOI |
6 | Sharifzadeh, M., Kolivand, F., Ghorbani, M. and Yasrobi, S. (2013), "Design of sequential excavation method for large span urban tunnels in soft ground-Niayesh tunnel", Tunn. Undergr. Sp. Tech., 35, 178-188. https://doi.org/10.1016/j.tust.2013.01.002 DOI |
7 | Ren, X. and Yu, X. (2011), "Multivariate statistical analysis (Version 2)", China Statistics Press, Beijing, China |
8 | Xu, Z.G., Cai, N.G., Li, X.F., Xian, M.T. and Dong, T.W. (2021), "Risk assessment of loess tunnel collapse during construction based on an attribute recognition model", Bull. Eng. Geology Environ., 80, 6205-6220. https://doi.org/10.1007/s10064-021-02300-8. DOI |
9 | Burland, J.B. (1990), "On the compressibility and shear strength of natural clay, Rankine lecture", Geotechnique, 40(3), 329-378. https://doi.org/10.1680/geot.1990.40.3.329. DOI |
10 | Xie, Z. (2010), "Matlab statistical analysis and application: 40 case studies", Beihang University Press, Beijing,China |
11 | Xue, Y., Zhang, X., Li, S., Qiu, D., Su, M., Li, L., Li, Z. and Tao, Y. (2018a), "Analysis of factors influencing tunnel deformation in loess deposits by data mining: A deformation prediction model", Eng. Geology, 232, 94-103. https://doi.org/10.1016/j.enggeo.2017.11.014 DOI |
12 | Xue, Y.G., Bai, C.H., Qiu, D.H., Kong, F.M. and Li, Z.Q. (2020) "Predicting rockburst with database using particle swarm optimization and extreme learning machine", Tunn. Undergr. Sp. Tech., 98, https://doi.org/10.1016/j.tust.2020.103287. DOI |
13 | Xue, Y.G., Zhang, X.L., Li, S.C., Qiu, D.H., Su, M.X., Li, L.P., Li, Z.Q. and Tao, Y.F. (2018b), "Analysis of factors influencing tunnel deformation in loess deposits by data mining: A deformation prediction model", Eng. Geology, 232, 94-103. https://doi.org/10.1016/j.enggeo.2017.11.014. DOI |
14 | Joshaghani, A., Balapour, M. and Ramezanianpour, A.A. (2018), "Effect of controlled environmental conditions on mechanical, microstructural and durability properties of cement mortar", Constr. Build. Mater., 164, 134-149. https://doi.org/10.1016/j.conbuildmat.2017.12.206. DOI |
15 | Specht, D.F. (1990), "Probabilistic neural networks and the polynomial adaline as complementary techniques for classification", IEEE T. Neural Networ., 1, 111-121, https://doi.org/10.1109/72.80210 DOI |
16 | Zhang, C.F., Peng, K.X. and Dong, J. (2020), "An incipient fault detection and self-learning identification method based on robust svdd and rbm-pnn", J. Process Control, 85, 173-183, https://doi.org/10.1016/j.jprocont.2019.12.002. DOI |
17 | Zhang, X.L., Xue, Y.G., Qiu, D.H., Yang, W.M., Su, M.X., Li, Z.Q. and Zhou, B.H. (2019), "Multi-index classification model for loess deposits based on rough set and bp neural network", Polish J. Environ. Studies, 28, 953-963, https://doi.org/10.15244/pjoes/85303. DOI |
18 | Lu, Q., Xiao, Z.P., Ji, J., Zheng, J. and Shang, Y.Q. (2017), "Moving least squares method for reliability assessment of rock tunnel excavation considering ground-support interaction", Comput. Geotech., 84, 88-100, https://doi.org/10.1016/j.compgeo.2016.11.019. DOI |
19 | Zhao, Y., Li, G. and Yu, Y. (2011), "Loess tunnel engineering", China Railway Press, Beijing, China. |
20 | Hotelling, H. (1933), "Analysis of a complex of statistical variables into principal components", J. Educational Psychology, 24, 417-441. https://doi.org/10.1037/h0071325. DOI |
21 | Kruse, G., Dijkstra, T. and Schokking, F. (2007), "Effects of soil structure on soil behaviour: Illustrated with loess, glacially loaded clay and simulated flaser bedding examples", Eng. Geology, 91, 34-45. https://doi.org/10.1016/j.enggeo.2006.12.011. DOI |
22 | Li, Y.R. (2018), "A review of shear and tensile strengths of the malan loess in china", Eng. Geology, 236, 4-10. https://doi.org/10.1016/j.enggeo.2017.02.023. DOI |
23 | Tuo, D.F., Xu, M.X., Li, Q. and Liu, S.H. (2017), "Soil aggregate stability and associated structure affected by long-term fertilization for a loessial soil on the loess plateau of china", Polish J. Environ. Studies, 26, 827-835. https://doi.org/10.15244/pjoes/66716. DOI |
24 | Yates, K., Fenton, C.H. and Bell, D.H. (2018), "A review of the geotechnical characteristics of loess and loess-derived soils from canterbury, south island, new Zealand", Eng. Geology, 236, 11-21, https://doi.org/10.1016/j.enggeo.2017.08.001. DOI |
25 | Faradonbeh, R.S. and Taheri, A. (2019), "Long-term prediction of rockburst hazard in deep underground openings using three robust data mining techniques", Eng. with Comput., 35, 659-675, https://doi.org/10.1007/s00366-018-0624-4. DOI |
26 | Chen, M. (2013), "Matlab neural network principles and detailed examples", Tsinghua University Press, Beijing, China |
27 | Cui, G.Y., Ma, J.F. and Wang, D.Y. (2021), "A large 3D laboratory test on the deformation characteristic of shallow loess tunnel under different plastic states", Bull. Eng. Geology Environ., 80, 7577-7590 DOI |
28 | Ding, H.H., Wu, Q., Zhao, D.K., Mu W.P. and Yu, S. (2019), "Risk assessment of karst collapse using an integrated fuzzy analytic hierarchy process and grey relational analysis model", Geomech. Eng., 18(5), 515-525, http://doi.org/10.12989/gae.2019.18.5.515. DOI |
29 | Feda, J. (1988), "Collapse of loess upon wetting", Eng. Geology, 25, 263-269. https://doi.org/10.1016/0013-7952(88)90031-2. DOI |
30 | Jiang, C., Zhang, H.Y., Zhang, Z.D. and Wang, D.W. (2019), "Model-based assessment soil loss by wind and water erosion in China's Loess Plateau: Dynamic change, conservation effectiveness, and strategies for sustainable restoration", Global Planetary Change, 172, 396-413. https://doi.org/10.1016/j.gloplacha.2018.11.002. DOI |
31 | Fernandez-Delgado, M., Cernadas, E., Barro, S. and Amorim, D. (2014), "Do we need hundreds of classifiers to solve real world classification problems?", J. Machine Learning Res., 15, 3133-3181 |
32 | Ng, C.W.W., Hong, Y., Liu, G.B. and Liu, T. (2012), "Ground deformations and soil-structure interaction of a multi-propped excavation in shanghai soft clays", Geotechnique, 62, 907-921, https://doi.org/10.1680/geot.10.P.072. DOI |
33 | Pu, Y.Y., Apel, D.B. and Xu, H.W. (2019), "Rockburst prediction in kimberlite with unsupervised learning method and support vector classifier", Tunn. Undergr. Sp. Tech., 90, 12-18. https://doi.org/10.1016/j.tust.2019.04.019. DOI |
34 | Din, N., Zhang, H. and Saeed, W. (2020), "Porosity prediction from model-based seismic inversion by using probabilistic neural network (pnn) in mehar block, pakistan", Episodes, 43(4), 935-946. https://doi.org/10.18814/epiiugs/2020/020055. DOI |
35 | Fatemi, S.A., Ahmadi, M. and Rostami, J. (2018), "Evaluation of tbm performance prediction models and sensitivity analysis of input parameters", Bull. Eng. Geology Environ., 77, 501-513. https://doi.org/10.1007/s10064-016-0967-2. DOI |
36 | Feng, S.J., Du, F.L., Shi, Z.M., Shui, W.H. and Tan, K. (2015), "Field study on the reinforcement of collapsible loess using dynamic compaction", Eng. Geology, 185, 105-115, https://doi.org/10.1016/j.enggeo.2014.12.006. DOI |
37 | Cochrane, P. and Weatherall, D.J. (1972), "The variation of neutrophil alkaline phosphatase during the menstrual cycle", J. Obstet. Gynaecol. Br. Commonw., 79, 1002-1008, https://doi.org/10.1111/j.1471-0528.1972.tb11878.x. DOI |
38 | Adams, M. (1971), "The single woman in today's society: A reappraisal", Am. J. Orthopsychiatry, 41, 776-786. https://doi.org/10.1111/j.1939-0025.1971.tb00741.x. DOI |
39 | Wang, C.L., Li, C.F., Chen, Z., Liao, Z.F., Zhao, G.M., Shi, F. and Yu, W.J. (2020), "Experimental investigation on multi-parameter classification predicting degradation model for rock failure using bayesian method", Geomech. Eng., 20(2), 113-120. https://doi.org/10.12989/gae.2020.20.2.113 DOI |
40 | Witten, I.H. and Frank, E. (2002), "Data mining: Practical machine learning tools and techniques with Java implementations", ACM SIGMOD Record, 31(1), 76-77, https://doi.org/10.1145/507338.507355. DOI |
41 | Chen, N., Sun, F.C., Ding, L.G. and Wang, H.Q. (2019), "An adaptive pnn-ds approach to classification using multi-sensor information fusion", Neural Comput. Appl., 31, 693-705. https://doi.org/10.1007/s00521-008-0221-3. DOI |
42 | Pawlak, Z. (1998), "Rough set theory and its applications to data analysis", Cybernetics Syst., 29(7), 661-688. https://doi.org/10.1080/019697298125470. DOI |
43 | Grzymala-Busse, J.W. and Ziarko, W. (2000), "Data mining and rough set theory", Commun. ACM, 43(4), 108-109. https://doi.org/10.1145/332051.332082. DOI |