Razvarz, S and Jafari, R orcid.org/0000-0001-7298-2363 (2017) Intelligent Techniques for Photocatalytic Removal of Pollution in Wastewater. Journal of Electrical Engineering, 5 (6). pp. 321-328. ISSN 2328-2223
Abstract
This paper discusses the elimination of C.I. AY23 (Acid Yellow 23) using UV/Ag-TiO2 process. To anticipate the photocatalytic elimination of AY23 with the existence of Ag-TiO2 nanoparticles processed under desired circumstances, two computational techniques namely NN (neural network) and PSO (particle swarm optimization) modeling are developed. A summed up of 100 data are used to establish the models, wherein introductory concentration of dye, UV light intensity, initial dosage of nano Ag-TiO2 and irradiation time are the four parameters applied as the input variables and elimination of AY23 as the output variable. The comparison among the predicted results by designed models and the experimental data proves that the performance of the NN model is comparatively sophisticated than the PSO model.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc/4.0/. |
Keywords: | Modeling, NN, PSO |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Arts, Humanities and Cultures (Leeds) > School of Design (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 28 Jan 2020 13:47 |
Last Modified: | 25 Jun 2023 22:08 |
Status: | Published |
Publisher: | David Publishing |
Identification Number: | 10.17265/2328-2223/2017.06.004 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:156078 |