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Clogging of slurry-shield tunnel-boring machine drives in sedimentary soft rock: A case study
Frontiers of Structural and Civil Engineering doi: 10.1007/s11709-023-0984-8
Keywords: slurry-shield TBM geological investigation clogging argillaceous siltstone TBM performance mitigation measures
Jon Hurt, Claudio Cimiotti
Engineering 2017, Volume 3, Issue 6, Pages 880-887 doi: 10.1016/j.eng.2017.11.007
Keywords: Sub-aqueous tunneling Tunnel-boring machine excavation Water intakes
QPSO-ILF-ANN-based optimization of TBM control parameters considering tunneling energy efficiency
Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 1, Pages 25-36 doi: 10.1007/s11709-022-0908-z
Keywords: tunnel boring machine control parameter optimization quantum particle swarm optimization artificial
Frontiers of Structural and Civil Engineering Pages 1370-1386 doi: 10.1007/s11709-023-0947-0
Keywords: tunnel boring machine hard-rock cutting free face disc cutter rock-cutting efficiency
A new method for boring of non-circular holes
ZHANG Kai, HU De-jin
Frontiers of Mechanical Engineering 2006, Volume 1, Issue 4, Pages 456-460 doi: 10.1007/s11465-006-0058-3
Keywords: electromagnetic actuation control method displacement flexible body revolving electromagnetic
Challenges of human–machine collaboration in risky decision-making
Frontiers of Engineering Management 2022, Volume 9, Issue 1, Pages 89-103 doi: 10.1007/s42524-021-0182-0
Keywords: human–machine collaboration risky decision-making human–machine team and interaction task allocation human–machine relationship
Spatial prediction of soil contamination based on machine learning: a review
Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 8, doi: 10.1007/s11783-023-1693-1
● A review of machine learning (ML) for spatial prediction of soil
Keywords: Soil contamination Machine learning Prediction Spatial distribution
Predicting the elemental compositions of solid waste using ATR-FTIR and machine learning
Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 10, doi: 10.1007/s11783-023-1721-1
● A method based on ATR-FTIR and ML was developed to predict CHNS contents in waste.
Keywords: Elemental composition Infrared spectroscopy Machine learning Moisture interference Solid waste Spectral
State-of-the-art applications of machine learning in the life cycle of solid waste management
Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 4, doi: 10.1007/s11783-023-1644-x
● State-of-the-art applications of machine learning (ML) in solid waste
Keywords: Machine learning (ML) Solid waste (SW) Bibliometrics SW management Energy utilization Life cycle
Luosi WEI, Zongxia JIAO
Frontiers of Mechanical Engineering 2009, Volume 4, Issue 2, Pages 184-191 doi: 10.1007/s11465-009-0034-9
Keywords: machine vision visual location solder paste printing VisionPro
Elucidate long-term changes of ozone in Shanghai based on an integrated machine learning method
Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 11, doi: 10.1007/s11783-023-1738-5
● A novel integrated machine learning method to analyze O3
Keywords: Ozone Integrated method Machine learning
Evaluation and prediction of slope stability using machine learning approaches
Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 4, Pages 821-833 doi: 10.1007/s11709-021-0742-8
Keywords: slope stability factor of safety regression machine learning repeated cross-validation
Liquefaction prediction using support vector machine model based on cone penetration data
Pijush SAMUI
Frontiers of Structural and Civil Engineering 2013, Volume 7, Issue 1, Pages 72-82 doi: 10.1007/s11709-013-0185-y
Keywords: earthquake cone penetration test liquefaction support vector machine (SVM) prediction
Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 2, Pages 183-197 doi: 10.1007/s11705-021-2073-7
Keywords: machine learning flowsheet simulations constraints exploration
Big data and machine learning: A roadmap towards smart plants
Frontiers of Engineering Management Pages 623-639 doi: 10.1007/s42524-022-0218-0
Keywords: big data machine learning artificial intelligence smart sensor cyber–physical system Industry 4.0
Title Author Date Type Operation
Clogging of slurry-shield tunnel-boring machine drives in sedimentary soft rock: A case study
Journal Article
QPSO-ILF-ANN-based optimization of TBM control parameters considering tunneling energy efficiency
Journal Article
Field and laboratory experimental studies on hard-rock tunnel excavation based on disc cutter coupled with high-pressure waterjet
Journal Article
Predicting the elemental compositions of solid waste using ATR-FTIR and machine learning
Journal Article
State-of-the-art applications of machine learning in the life cycle of solid waste management
Journal Article
Research and application of visual location technology for solder paste printing based on machine vision
Luosi WEI, Zongxia JIAO
Journal Article
Elucidate long-term changes of ozone in Shanghai based on an integrated machine learning method
Journal Article
Liquefaction prediction using support vector machine model based on cone penetration data
Pijush SAMUI
Journal Article
Using machine learning models to explore the solution space of large nonlinear systems underlying flowsheet
Journal Article