記事
Future of Machine Learning in Geotechnics (FOMLIG), 5–6 Dec 2023, Okayama, Japan
デジタルデータあり（Crossref）
すぐに読む
CiNii Research
Future of Machine Learning in Geotechnics (FOMLIG), 5–6 Dec 2023, Okayama, Japan
- 資料種別
- 記事
- 著者
- Kok-Kwang Phoonほか
- 出版者
- Informa UK Limited
- 出版年
- 2024-01-02
- 資料形態
- デジタル
- 掲載誌名
- Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards 18 1
- 掲載ページ
- p.288-303
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デジタル
- 資料種別
- 記事
- 著者標目
- 出版年月日等
- 2024-01-02
- 出版年（W3CDTF）
- 2024-01-02
- タイトル（掲載誌）
- Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards
- 巻号年月日等（掲載誌）
- 18 1
- 掲載巻
- 18
- 掲載号
- 1
- 掲載ページ
- 288-303
- 掲載年月日（W3CDTF）
- 2024-01-02
- ISSN（掲載誌）
- 17499518
- 出版事項（掲載誌）
- Informa UK Limited
- 対象利用者
- 一般
- DOI
- 10.1080/17499518.2024.2316882
- 作成日（W3CDTF）
- 2024-02-26
- 参照
- Reliability analysis of soil-geogrid pullout models in JapanPhysics-informed machine learningUnpacking data-centric geotechnicsEditorial for Advances and applications of deep learning and soft computing in geotechnical underground engineeringComparison of trend models for geotechnical spatial variability: Sparse Bayesian Learning vs. Gaussian Process RegressionA machine learning–based approach to regional‐scale mapping of sensitive glaciomarine clay combining airborne electromagnetics and geotechnical dataStatistical evaluation and calibration of two methods for predicting nail loads of soil nail walls in ChinaInterpolation of extremely sparse geo-data by data fusion and collaborative Bayesian compressive samplingSimilarity quantification of soil spatial variability between two cross-sections using auto-correlation functionsA database of installation monitoring and uplift load tests of round-shaft helical anchors in BrazilStatistical Analyses on a Database of Deep Excavations in Shanghai Soft Clays in China from 1995–2018Settlement of Shallow Foundations on Clay—A Database StudyCross-project utilisation of tunnel boring machine (TBM) construction data: a case study using big data from Yin-Song diversion project in ChinaFuture-proofing geotechnics workflows: accelerating problem-solving with large language modelsReal-time fusion of multi-source monitoring data with geotechnical numerical model results using data-driven and physics-informed sparse dictionary learningDevelopment of an integrated Web-based system with a pile load test database and pre-analyzed data<b>A database to ensure reliability of bored pile design in Egypt</b>Bored piles in tropical soils and rocks: shaft and base resistances, <i>t–z</i> and <i>q–w</i> modelsEditorialReliability-Based Geotechnical Resistance Factors for Axially Loaded MicropilesPractical recommendations for machine learning in underground rock engineering – On algorithm development, data balancing, and input variable selectionMachine learning-enhanced soil classification by integrating borehole and CPTU data with noise filteringDesign and implementation of a drilled shaft load test databaseIntelligent Monitoring System Based on Spatio–Temporal Data for Underground Space InfrastructureModifying the Tailored Clustering Enabled Regionalization (TCER) framework for outlier site detection and inference efficiencyWhen is the observational method in geotechnical engineering favourable?Wall and Ground Movements due to Deep Excavations in Shanghai Soft SoilsReport for ISSMGE TC309/TC304/TC222 Third ML dialogue on “Data-Driven Site Characterization (DDSC)”Special issue on “Machine learning and AI in geotechnics”Detection of outliers with respect to a MUSIC geotechnical databaseEthics and Safety of Human-Machine TeamingProbabilistic Inverse Analysis for GeotechnicsVariability of Predictions in GeotechnicsEvaluation of compression interpretation criteria for drilled shafts socketed into rocksInstrumented concrete pile tests – part 1: a review of instrumentation and proceduresEditorial for Special Issue “Applications of Artificial Intelligence and Machine Learning in Geotechnical Engineering”Federated machine learning in data-protection-compliant researchChallenges in data-driven site characterizationImproved Simplified Method for Prediction of Loads in Reinforced Soil WallsLoad and Resistance Factor Design (LRFD) for Driven Piles Using Dynamic Methods—A Florida PerspectiveStatistics of model factors in reliability-based design of axially loaded driven piles in sandEvaluation of model uncertainties in reliability-based design of steel H-piles in axial compressionData-driven approximation of geotechnical dynamics to an equivalent single-degree-of-freedom vibration system based on dynamic mode decompositionMachine learning method for CPTu based 3D stratification of New Zealand geotechnical database sitesStatistical prediction of deformations of soil nail wallsEvaluation of interpretation criteria for drilled shafts with tip post-groutingCharacterization of Model Uncertainty in the Static Pile Design FormulaStatistical Analyses of Model Factors in Reliability-Based Limit-State Design of Drilled Shafts under Axial LoadingWhat Geotechnical Engineers Want to Know about ReliabilityBenchmarking Data-Driven Site CharacterizationData analytics in geotechnical and geological engineeringA hybrid physical data informed DNN in axial displacement prediction of immersed tunnel jointA real-time intelligent classification model using machine learning for tunnel surrounding rock and its applicationProbabilistic characterization of two-dimensional soil profile by integrating cone penetration test (CPT) with multi-channel analysis of surface wave (MASW) dataAnalysis of a database of open pit mine slope failures to predict travel distance, setback distance, and geometric propertiesDeep learning applications for wind farms site characterization and monitoringModel factor for the bearing capacity of piles from pressuremeter test results – Eurocode 7 approachTransfer Learning for Improving Seismic Building Damage AssessmentHelical Pile Capacity-to-Torque Correlation: A More Reliable Capacity-to-Torque Factor Based on Full Scale Load TestsAxial Load Capacity Predictions of Drilled Displacement Piles With SPT- and CPT-based Direct MethodsStatistical assessment of load model accuracy for steel grid-reinforced soil wallsAnalysis and calibration of default steel strip pullout models used in JapanTrend estimation and layer boundary detection in depth-dependent soil data using sparse Bayesian lassoThe story of statistics in geotechnical engineeringInfluence of model type, bias and input parameter variability on reliability analysis for simple limit states in soil–structure interaction problemsCharacterization of model uncertainty in predicting axial resistance of piles driven into clayNon-parametric modelling and simulation of spatiotemporally varying geo-dataData-driven subsurface modelling using a Markov random field modelFuture of machine learning in geotechnicsReport for ISSMGE TC309/TC304/TC222 and ASCE Geo-Institute Risk Assessment and Management Committee Fourth Machine Learning in Geotechnics Dialogue on “Machine Learning Supremacy Projects”Big Data in the construction industry: A review of present status, opportunities, and future trendsPhysics-informed machine learning for reliability and systems safety applications: State of the art and challengesAnalysis of Soil-Steel Bar Mat Pullout Models Using a Statistical ApproachLRFD Design and Construction of Shallow Foundations for Highway Bridge StructuresReliability analysis of geogrid installation damage test data in JapanPromises and trust in human–robot interactionBenchmark examples for data-driven site characterisationStatistical evaluation of model factors in reliability calibration of high-displacement helical piles under axial loadingQuasi-site-specific multivariate probability distribution model for sparse, incomplete, and three-dimensional spatially varying soil dataStatistics of Model Factors and Consideration in Reliability-Based Design of Axially Loaded Helical PilesExpanded Database Assessment of Design Methods for Spread Foundations under Axial Compression and Uplift LoadingQuasi-site-specific soil property prediction using a cluster-based hierarchical Bayesian modelComparison of Data-Driven Site Characterization Methods through Benchmarking: Methodological and Application AspectsA Bayesian unsupervised learning approach for identifying soil stratification using cone penetration dataConstructing Quasi-Site-Specific Multivariate Probability Distribution Using Hierarchical Bayesian ModelA Hierarchical Bayesian Similarity Measure for Geotechnical Site RetrievalDevelopment of Subsurface Geological Cross-Section from Limited Site-Specific Boreholes and Prior Geological Knowledge Using Iterative Convolution XGBoostSpecial Issue: Data-Driven Discovery in Geosciences: Opportunities and ChallengesStatistical calibration of federal highway administration simplified models for facing tensile forces of soil nail wallsData-driven and physics-informed Bayesian learning of spatiotemporally varying consolidation settlement from sparse site investigation and settlement monitoring dataEstablishing region-specific N – V relationships through hierarchical Bayesian modelingIntroducing <i>Data-Centric Engineering</i>: An open access journal dedicated to the transformation of engineering design and practiceMeta-Analysis of 301 Slope Failure Calculations. I: Database DescriptionBayesian Learning Methods for Geotechnical DataCharacterisation for spatial distribution of mining-induced stress through deep learning algorithm on SHM dataDesign method reliability assessment from an extended database of axial load tests on piles driven in sandUltimate limit state reliability-based design of augered cast-in-place piles considering lower-bound capacitiesBig Data in Construction: Current Applications and Future OpportunitiesCharacteristics of Unified Databases for Driven PilesConstructing a Site-Specific Multivariate Probability Distribution Using Sparse, Incomplete, and Spatially Variable (MUSIC-X) DataEstimation of trend and random components of conditional random field using Gaussian process regressionStatistical analysis of the effective stress method and modifications for prediction of ultimate bond strength of soil nailsReliability analysis of geogrid creep data in JapanSupported Excavations: Observational Method and Inverse ModelingRole of the Calculated Risk in Earthwork and Foundation EngineeringConstructing Site-Specific Multivariate Probability Distribution Model Using Bayesian Machine LearningDatabase for Retaining Wall and Ground Movements due to Deep ExcavationsBayesian identification of soil stratigraphy based on soil behaviour type indexRole of reliability calculations in geotechnical designMeasuring Similarity between Site-Specific Data and Records from Other SitesQuasi-site-specific prediction for deformation modulus of rock massStatistical Evaluation of the FHWA Simplified Method and Modifications for Predicting Soil Nail LoadsToward Human-in-the-Loop Construction Robotics: Understanding Workers’ Response Through Trust Measurement During Human-Robot CollaborationReliability in Geotechnical Design – Some Fundamentals.(<小特集>IS-TOULOUSE 2002「軟弱地盤における地下建設の工学的諸問題」)
- 参照（URI）
- 連携機関・データベース
- 国立情報学研究所 : CiNii Research
- 提供元機関・データベース
- Crossref科学研究費助成事業データベース