Novel approach to estimate vertical scale of fluctuation based on CPT data using convolutional neural networks
出版年份 2021 全文链接
标题
Novel approach to estimate vertical scale of fluctuation based on CPT data using convolutional neural networks
作者
关键词
Scale of fluctuation, Convolutional neural network, Inherent spatial variability, Random fields
出版物
ENGINEERING GEOLOGY
Volume 294, Issue -, Pages 106342
出版商
Elsevier BV
发表日期
2021-08-25
DOI
10.1016/j.enggeo.2021.106342
参考文献
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- (2021) Yejin Kim et al. ENGINEERING GEOLOGY
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- (2021) Haojie Wang et al. ENGINEERING GEOLOGY
- Towards semi-automatic discontinuity characterization in rock tunnel faces using 3D point clouds
- (2021) Jiayao Chen et al. ENGINEERING GEOLOGY
- Automated extraction and evaluation of fracture trace maps from rock tunnel face images via deep learning
- (2021) Jiayao Chen et al. INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES
- Quantitative evaluation of geological uncertainty and its influence on tunnel structural performance using improved coupled Markov chain
- (2021) Jin-Zhang Zhang et al. Acta Geotechnica
- Modelling the performance of EPB shield tunnelling using machine and deep learning algorithms
- (2021) Song-Shun Lin et al. Geoscience Frontiers
- Evaluation of bridge decks with overlays using impact echo, a deep learning approach
- (2020) Sattar Dorafshan et al. AUTOMATION IN CONSTRUCTION
- Shear loading detection of through bolts in bridge structures using a percussion‐based one‐dimensional memory‐augmented convolutional neural network
- (2020) Furui Wang et al. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
- Meta-modelling of coupled thermo-hydro-mechanical behaviour of hydrate reservoir
- (2020) Mingliang Zhou et al. COMPUTERS AND GEOTECHNICS
- Simulation of non-stationary non-Gaussian random fields from sparse measurements using Bayesian compressive sampling and Karhunen-Loève expansion
- (2019) Silvana Montoya-Noguera et al. STRUCTURAL SAFETY
- Identification of sample path smoothness in soil spatial variability
- (2019) Jianye Ching et al. STRUCTURAL SAFETY
- Interpolation and stratification of multilayer soil property profile from sparse measurements using machine learning methods
- (2019) Tengyuan Zhao et al. ENGINEERING GEOLOGY
- Deep learning–based image instance segmentation for moisture marks of shield tunnel lining
- (2019) Shuai Zhao et al. TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
- Direct simulation of random field samples from sparsely measured geotechnical data with consideration of uncertainty in interpretation
- (2018) Yu Wang et al. CANADIAN GEOTECHNICAL JOURNAL
- Effect of spatial variability of shear strength parameters on critical slip surfaces of slopes
- (2018) Xiao-Hui Qi et al. ENGINEERING GEOLOGY
- Vertical spatial correlation length based on standard penetration tests
- (2018) Emir Ahmet Oguz et al. MARINE GEORESOURCES & GEOTECHNOLOGY
- A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load
- (2018) Wei Zhang et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Deep learning based image recognition for crack and leakage defects of metro shield tunnel
- (2018) Hong-wei Huang et al. TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
- Simulation of Random Fields with Trend from Sparse Measurements without Detrending
- (2018) Yu Wang et al. JOURNAL OF ENGINEERING MECHANICS
- Influence of spatial variability of soil Young's modulus on tunnel convergence in soft soils
- (2017) H.W. Huang et al. ENGINEERING GEOLOGY
- Evaluation of the maximum horizontal displacement around the power station caverns using artificial neural network
- (2017) Morteza Rajabi et al. TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
- Random field characterization of uniaxial compressive strength and elastic modulus for intact rocks
- (2017) Hua-Xin Liu et al. Geoscience Frontiers
- Evaluation of the scale of fluctuation of geotechnical parameters by autocorrelation function and semivariogram function
- (2016) Site Onyejekwe et al. ENGINEERING GEOLOGY
- Random finite element method for spudcan foundations in spatially variable soils
- (2016) J.H. Li et al. ENGINEERING GEOLOGY
- Evaluation of spatial soil variability in the Pearl River Estuary using CPTU data
- (2016) Emanuel Bombasaro et al. SOILS AND FOUNDATIONS
- Bayesian model comparison and selection of spatial correlation functions for soil parameters
- (2014) Zijun Cao et al. STRUCTURAL SAFETY
- Reliability Analysis of Load and Resistance Factor Design of Slopes
- (2013) Rodrigo Salgado et al. JOURNAL OF GEOTECHNICAL AND GEOENVIRONMENTAL ENGINEERING
- Effect of spatial correlation of standard penetration test (SPT) data on bearing capacity of driven piles in sand
- (2012) Lianyang Zhang et al. CANADIAN GEOTECHNICAL JOURNAL
- Bayesian Approach for Probabilistic Site Characterization Using Cone Penetration Tests
- (2012) Zijun Cao et al. JOURNAL OF GEOTECHNICAL AND GEOENVIRONMENTAL ENGINEERING
- Comparison of different probabilistic methods for predicting stability of a slope in spatially variable c– soil
- (2009) R. Suchomel et al. COMPUTERS AND GEOTECHNICS
- Spatial correlation structures of CPT data in a liquefaction site
- (2009) Chia Nan Liu et al. ENGINEERING GEOLOGY
- Design of laterally loaded piles in clays based on cone penetration test data: a reliability-based approach
- (2009) S. HALDAR et al. GEOTECHNIQUE
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