Backpropagation neural networks modelling of photocatalytic degradation of organic pollutants using TiO2-based photocatalysts
Backpropagation; Catalysts; Chemical industry; Degradation; Ketones; Network architecture; Neural networks; Photocatalysts; Polycyclic aromatic hydrocarbons; Silver compounds; Titanium dioxide; Titanium oxides; Advanced Oxidation Processes; Back propagation artificial neural network (BPANN); Back pr...
Saved in:
Main Authors: | Ayodele B.V., Alsaffar M.A., Mustapa S.I., Vo D.-V.N. |
---|---|
Other Authors: | 56862160400 |
Format: | Article |
Published: |
John Wiley and Sons Ltd
2023
|
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A critical analysis of modification effects on nanostructured TiO2-based photocatalysts for hydrogen production
by: Ayodele B.V., et al.
Published: (2023) -
Modeling the effect of process parameters on the photocatalytic degradation of organic pollutants using artificial neural networks
by: Ayodele B.V., et al.
Published: (2023) -
Modeling the photocatalytic degradation of 1,2-Dihydroxybenzene using Multilayer Perceptron Neural Networks
by: Alsaffar M.A., et al.
Published: (2023) -
Recent advances in photocatalyst for photocatalytic degradation of organic pollutants : Short review
by: Ros Shazuin Rayyanu, Mohd Zaki, et al.
Published: (2022) -
Recent advances in TiO2/ZnS-based binary and ternary photocatalysts for the degradation of organic pollutants
by: Devagi, Kanakaraju, et al.
Published: (2023)