Machine learning of three-dimensional subsurface geological model for a reclamation site in Hong Kong
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[1] Chao Shi,et al. Data-driven sequential development of geological cross-sections along tunnel trajectory , 2022, Acta Geotechnica.
[2] Yu Wang,et al. Data-driven construction of Three-dimensional subsurface geological models from limited Site-specific boreholes and prior geological knowledge for underground digital twin , 2022, Tunnelling and Underground Space Technology.
[3] X. Qi,et al. Two-dimensional prediction of the interface of geological formations: A comparative study , 2022, Tunnelling and Underground Space Technology.
[4] Wengang Zhang,et al. Rockhead profile simulation using an improved generation method of conditional random field , 2021, Journal of Rock Mechanics and Geotechnical Engineering.
[5] Yu Wang,et al. Training image selection for development of subsurface geological cross-section by conditional simulations , 2021, Engineering Geology.
[6] Jian-Min Zhang,et al. Machine learning method for CPTu based 3D stratification of New Zealand geotechnical database sites , 2021, Adv. Eng. Informatics.
[7] Yu Wang,et al. Development of Subsurface Geological Cross-Section from Limited Site-Specific Boreholes and Prior Geological Knowledge Using Iterative Convolution XGBoost , 2021 .
[8] K. Phoon,et al. Challenges in data-driven site characterization , 2021, Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards.
[9] Yu Wang,et al. Smart Determination of Borehole Number and Locations for Stability Analysis of Multi-layered Slopes using Multiple Point Statistics and Information Entropy , 2021 .
[10] Kok-Kwang Phoon,et al. 3D Probabilistic Site Characterization by Sparse Bayesian Learning , 2020 .
[11] Yu Wang,et al. Nonparametric and data-driven interpolation of subsurface soil stratigraphy from limited data using multiple point statistics , 2020, Canadian Geotechnical Journal.
[12] T. Lim. Housing Policies in Hong Kong , 2020 .
[13] J. Chu,et al. Prediction of interfaces of geological formations using the multivariate adaptive regression spline method , 2020, Underground Space.
[14] C. Juang,et al. Probabilistic analysis and design of stabilizing piles in slope considering stratigraphic uncertainty , 2019, Engineering Geology.
[15] Weihua Ming,et al. A Stratigraphic Prediction Method Based on Machine Learning , 2019, Applied Sciences.
[16] C. Lee,et al. Soft Soil Engineering , 2017 .
[17] Albert T. Yeung,et al. Statistical Analysis of geotechnical engineering properties of Hong Kong marine clays , 2017 .
[18] Ke Zhang,et al. A training image evaluation and selection method based on minimum data event distance for multiple-point geostatistics , 2017, Comput. Geosci..
[19] Tianqi Chen,et al. XGBoost: A Scalable Tree Boosting System , 2016, KDD.
[20] Albert T. Yeung,et al. Geotechnical works of the Hong Kong-Zhuhai-Macao Bridge Project , 2016 .
[21] G. Mariéthoz,et al. Multiple-point Geostatistics: Stochastic Modeling with Training Images , 2014 .
[22] Julián M. Ortiz,et al. Verifying the high-order consistency of training images with data for multiple-point geostatistics , 2014, Comput. Geosci..
[23] Jef Caers,et al. Modeling Uncertainty in the Earth Sciences , 2011 .
[24] R. Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .
[25] Clayton V. Deutsch,et al. Geostatistical Software Library and User's Guide , 1998 .
[26] Clayton V. Deutsch,et al. Hierarchical object-based stochastic modeling of fluvial reservoirs , 1996 .
[27] Anil K. Jain,et al. A modified Hausdorff distance for object matching , 1994, Proceedings of 12th International Conference on Pattern Recognition.
[28] Daniel P. Huttenlocher,et al. Comparing Images Using the Hausdorff Distance , 1993, IEEE Trans. Pattern Anal. Mach. Intell..
[29] R. Walsh,et al. Land reclamation in Singapore, Hong Kong and Macau , 1991 .
[30] A. Mood. The Distribution Theory of Runs , 1940 .
[31] Wengang Zhang,et al. Similarity quantification of soil parametric data and sites using confidence ellipses , 2022 .
[32] Yu Wang,et al. CPT-based subsurface soil classification and zonation in a 2D vertical cross-section using Bayesian compressive sampling , 2019 .
[33] Robert Y. Liang,et al. A hidden Markov random field model based approach for probabilistic site characterization using multiple cone penetration test data , 2018 .
[34] J. Swift,et al. Visualizing Land Reclamation in Hong Kong: A Web Application , 2014 .
[35] Steven F. Carle,et al. CONDITIONAL SIMULATION OF HYDROFACIES ARCHITECTURE: A TRANSITION PROBABILITY/MARKOV APPROACH1 , 1998 .
[36] R. M. Srivastava,et al. Multivariate Geostatistics: Beyond Bivariate Moments , 1993 .