Application of Machine Learning to Predict the Performance of an EMIPG Reactor Using Data from Numerical Simulations
Energies
; 15(7):2559, 2022.
Article
in English
| ProQuest Central | ID: covidwho-1785586
Energy; microwave induced plasma gasification; CFD modeling; machine learning; ANN; GBM; Organic chemicals; Medical wastes; Population; Plasma; Software packages; Reduced order models; Hydrodynamics; Reactors; Models; Fluid dynamics; Electrodes; Open source software; Emissions; Solid wastes; Fluid flow; Clean energy; Computer applications; Industrial wastes; Byproducts; Synthesis gas; Landfill; Gasification; Two dimensional models; Learning algorithms; Computer simulation; COVID-19; User interface; Simulation; Airports; Renewable energy; Partial differential equations; Optimization; Waste to energy; Neural networks; Microwave plasmas; Mathematical models; Literature reviews; Algorithms; Computational fluid dynamics; Geometry; Data sets; Dioxins
Full text:
Available
Collection:
Databases of international organizations
Database:
ProQuest Central
Type of study:
Prognostic study
Language:
English
Journal:
Energies
Year:
2022
Document Type:
Article
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