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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
Advancing agriculture with machine learning: a new frontier in weed management
Frontiers of Agricultural Science and Engineering doi: 10.15302/J-FASE-2024564
● Machine learning offers innovative and sustainable weed management
Keywords: Weed management herbicides machine learning agricultural practices environmental impact
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
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
Predicting torsional capacity of reinforced concrete members by data-driven machine learning models
Frontiers of Structural and Civil Engineering 2024, Volume 18, Issue 3, Pages 444-460 doi: 10.1007/s11709-024-1050-x
Keywords: RC members torsional capacity machine learning models design codes
Improving lipid production by for renewable fuel production based on machine learning
Frontiers of Chemical Science and Engineering 2024, Volume 18, Issue 5, doi: 10.1007/s11705-024-2410-8
Keywords: microbial lipid machine learning artificial neural network support vector machine genetic algorithm
Big data and machine learning: A roadmap towards smart plants
Frontiers of Engineering Management 2022, Volume 9, Issue 4, 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
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
Frontiers of Structural and Civil Engineering 2024, Volume 18, Issue 2, Pages 294-308 doi: 10.1007/s11709-024-1045-7
Keywords: steel weld machine learning convolutional neural network weld defect detection classification task
Frontiers of Environmental Science & Engineering 2024, Volume 18, Issue 2, doi: 10.1007/s11783-024-1777-6
● A machine learning approach was applied to predict free chlorine
Keywords: Machine learning Data-driven modeling Drinking water treatment Disinfection Chlorination
Development of machine learning multi-city model for municipal solid waste generation prediction
Frontiers of Environmental Science & Engineering 2022, Volume 16, Issue 9, doi: 10.1007/s11783-022-1551-6
● A database of municipal solid waste (MSW) generation in China was established.
Keywords: Municipal solid waste Machine learning Multi-cities Gradient boost regression tree
Machine learning in building energy management: A critical review and future directions
Frontiers of Engineering Management 2022, Volume 9, Issue 2, Pages 239-256 doi: 10.1007/s42524-021-0181-1
Keywords: building energy management machine learning integrated framework knowledge evolution
Machine learning modeling identifies hypertrophic cardiomyopathy subtypes with genetic signature
Frontiers of Medicine 2023, Volume 17, Issue 4, Pages 768-780 doi: 10.1007/s11684-023-0982-1
Keywords: machine learning methods hypertrophic cardiomyopathy genetic risk
Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 12, doi: 10.1007/s11783-023-1752-7
● Online learning models accurately predict influent flow rate at
Keywords: Wastewater prediction Data stream Online learning Batch learning Influent flow rates
Title Author Date Type Operation
Elucidate long-term changes of ozone in Shanghai based on an integrated machine learning method
Journal Article
Using machine learning models to explore the solution space of large nonlinear systems underlying flowsheet
Journal Article
Predicting torsional capacity of reinforced concrete members by data-driven machine learning models
Journal Article
Improving lipid production by for renewable fuel production based on machine learning
Journal Article
State-of-the-art applications of machine learning in the life cycle of solid waste management
Journal Article
Automated identification of steel weld defects, a convolutional neural network improved machine learning
Journal Article
Development of gradient boosting-assisted machine learning data-driven model for free chlorine residual
Journal Article
Development of machine learning multi-city model for municipal solid waste generation prediction
Journal Article
Machine learning in building energy management: A critical review and future directions
Journal Article
Machine learning modeling identifies hypertrophic cardiomyopathy subtypes with genetic signature
Journal Article