科研论文 (Selected papers)

2022年成果 (Published papers in 2022)

  • Zhao T., Song C, and Xu, L*. (2022). “Prediction of UCS using fully Bayesian Gaussian process regression with model class selection”, Rock Mechanics and Rock Engineering, DOI: 10.1007/s00603-022-02964-y, online. (SCI, IF2021 = 6.518, JCR Q1).

  • Guan, Z., Wang, Y*., and Zhao, T. (2022). “Adaptive Sampling Strategy for Characterizing Spatial Distribution of Soil Liquefaction Potential Using Cone Penetration Test”. Journal of Rock Mechanics and Geotechnical Engineering, 14(4), 1221-1231. (SCI, IF2021 = 5.915, JCR Q1) 

  • 朱文清，赵腾远*，宋超，王宇，许领 (2022). 基于吉布斯采样与压缩感知的二维非平稳CPT 数据快速插值方法. 土木与环境工程学报 (中英文), (核心期刊，CSCD检索). 10.11835/j.issn.2096-6717.XXXX.XX.001.

2021年成果 (Published papers in 2021)

  • Zhao, T.*, Lei, Jieyang, Xu, Ling (2021). “An efficient Bayesian method for estimating runout distance of region-specific landslides using sparse data.” Georisk, 16(1), 140-153. (SCI, IF2020 = 3.868, JCR Q2)
  • Zhao, T*., Wang, Y., and Xu, L. (2021). “Efficient CPT locations for characterizing spatial variability of soil properties within a multilayer vertical cross-section using information entropy and Bayesian compressive sensing.” Computers and Geotechnics, 137, 104260. (SCI, IF2020 = 4.956, JCR Q1)
  • Zhao, T., Wang, Y*. (2021). "Statistical Interpolation of Spatially Varying but Sparsely Measured 3D Geo-Data Using Compressive Sensing and Variational Bayesian Inference." Math Geosci, 53(6), 1171-1199. (SCI, IF2020 = 2.576, JCR Q2)
  • Xu, L., Yan, D., and Zhao, T*. (2021). “Probabilistic evaluation of loess landslide impact using multivariate model.” Landslides, 18, 1011–1023, https://doi.org/10.1007/s10346-020-01521-4. (SCI, IF2020 = 6.578, JCR Q1)
  • Guan, Z., Wang, Y*., and Zhao, T. (2021). “Delineating the spatial distribution of soil liquefaction potential in a cross-section from limited cone penetration tests.” Soil Dynamics and Earthquake Engineering, 145, 106710. (SCI, IF2020 = 3.718 , JCR Q2)

2020年成果 (Published papers in 2020)

  • Zhao, T., and Wang, Y*. (2020). “Non-parametric simulation of non-stationary non-Gaussian 3D random field samples directly from sparse measurements using signal decomposition and Markov Chain Monte Carlo.” Reliability Engineering & System Safety, 203, 107087. (SCI, IF2020 = 6.188, JCR Q1)

  • Zhao, T., Xu, L., and Wang, Y*. (2020). “Fast non-parametric simulation of 2D non-stationary cone penetration test (CPT) data without pre-stratification using Markov Chain Monte Carlo simulation.” Engineering Geology, 273, 105670. (SCI, IF2020 = 6.755, JCR Q1)

  • Zhao, T., and Wang, Y*. (2020). “Differentiation of discrete data with unequal measurement intervals and quantification of uncertainty in differentiation using Bayesian compressive sampling.” Computers and Geotechnics, 122, 103537. (SCI, IF2020 = 4.956, JCR Q1)

  • Zhao, T., Wang Y*. (2020) “Interpolation and stratification of multilayer soil property profile from sparse measurements using machine learning methods.” Engineering Geology, 265, 105430. (SCI, IF2020 = 6.755, JCR Q1)

  • Wang, Y*., Hu, Y., and Zhao, T. (2020). “CPT-based subsurface soil classification and zonation in a 2D vertical cross-section using Bayesian compressive sampling.” Canadian Geotechnical Journal, 57(7): 947-958. (SCI, IF2019 = 2.802, JCR Q2)

  • Hu, Y., Wang, Y*., Zhao, T., and Phoon, K.K. (2020) “Bayesian supervised learning of site-specific geotechnical spatial variability from sparse measurements.” Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 6(2), 04020019. (SCI, IF2020 = 1.926, JCR Q3)

2019年成果 (Published papers in 2019)

  • Hu, Y., Zhao, T., Wang, Y*., Choi, C., and Ng, C. W. W. (2019). “Direct simulation of two-dimensional isotropic or anisotropic random field from sparse measurement using Bayesian compressive sampling.” Stochastic Environmental Research and Risk Assessment, 33, 8-9, 1477–1496. (SCI, IF2020 = 3.379, JCR Q1)

  • Montoya-Noguera, S., Zhao, T., Hu, Y., Wang, Y*., and Phoon, K.K. (2019). “Simulation of non-stationary non-Gaussian random fields from sparse measurements using Bayesian compressive sampling and Karhunen-Loève expansion.” Structural Safety, 79, 66-79. (SCI, IF2020 = 5.047, JCR Q1)

  • Wang, Y*., Zhao, T., Phoon, K.K (2019). “Statistical inference of random field auto-correlation structure from multiple sets of incomplete and sparse measurements using Bayesian compressive sampling-based bootstrapping”. Mechanical Systems and Signal Processing, 124, 217-236. (SCI, IF2020 = 6.823, Q1)