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Physical Sciences and Engineering Chemical Engineering Filtration and Separation

Sparse Bayesian learning for data driven polynomial chaos expansion with application to chemical processes

Article ID Journal Published Year Pages File Type
11003256 Chemical Engineering Research and Design 2018 13 Pages PDF
Keywords
Data drivenSynthesis gas productionPolynomial chaosNatural gas dehydrationUncertainty quantification
Related Topics
Physical Sciences and Engineering Chemical Engineering Filtration and Separation
Preview
Sparse Bayesian learning for data driven polynomial chaos expansion with application to chemical processes
Authors
Pham Luu Trung Duong, Le Quang Minh, Muhammad Abdul Qyyum, Moonyong Lee,
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Journal
Chemical Engineering Research and Design
Journal: Chemical Engineering Research and Design
Related Categories
Data driven
Synthesis gas production
Polynomial chaos
Natural gas dehydration
Uncertainty quantification
Bioengineering
Catalysis
Chemical Engineering (General)
Chemical Health and Safety
Colloid and Surface Chemistry
Filtration and Separation
Fluid Flow and Transfer Processes
Process Chemistry and Technology
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