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Plasmonic silver nanoparticles were deposited on TiO<jats:sub>2<\/jats:sub> nanosheets\/reduced graphene oxide nanocomposite via a photodeposition method (TGA(<jats:italic>x<\/jats:italic>) samples). The as\u2010obtained samples were identified by variety of techniques such as XRD, UV\u2010Vis DRS, FESEM\/EDX, TEM, and Raman spectroscopy. The photocatalytic degradation experiments of TC (in concentration of 30\u00a0mg\/L) were carried out by synthesized nanocomposites, and the degradation efficiency of TGA (0.076) (the optimal sample) was evaluated as 52.56% after 3\u00a0hr of irradiation under visible light. The obtained results showed that in TGA(<jats:italic>x<\/jats:italic>) samples, the reduced graphene oxide acts as a bridge for transferring photoinduced electrons from plasmonic silver nanoparticles to TiO<jats:sub>2<\/jats:sub> nanosheetes. A three\u2010layered artificial neural network model with four input variables (irradiation time, catalyst dosage, initial concentration of TC, and silver nitrate content) and one output variable (% degradation) was optimized with 11 hidden neurons. The relative importance of the independent variables was calculated using Garson formula and the initial concentration of TC was found as the most influencing parameter (relative importance of 31%) on the treatment efficiency.<\/jats:p><\/jats:sec><jats:sec><jats:title>Practitioner points<\/jats:title><jats:p>\n<jats:list list-type=\"bullet\">\n\n<jats:list-item><jats:p>TiO<jats:sub>2<\/jats:sub> nanosheets synthesized on the reduced graphene oxide by hydrothermal method.<\/jats:p><\/jats:list-item>\n\n<jats:list-item><jats:p>Plasmonic silver nanoparticles deposited on TNs\/rGO by photodeposition method<\/jats:p><\/jats:list-item>\n\n<jats:list-item><jats:p>The photocatalytic degradation of tetracycline (TC) was modeled by artificial neural network.<\/jats:p><\/jats:list-item>\n<\/jats:list>\n<\/jats:p><\/jats:sec>","DOI":"10.1002\/wer.1258","type":"journal-article","created":{"date-parts":[[2019,10,19]],"date-time":"2019-10-19T18:15:00Z","timestamp":1571508900000},"page":"662-676","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Photocatalytic treatment of tetracycline antibiotic wastewater by silver\/TiO<sub>2<\/sub> nanosheets\/reduced graphene oxide and artificial neural network modeling"],"prefix":"10.1002","volume":"92","author":[{"given":"Fatemeh\u2010Sadat","family":"Tabatabai\u2010Yazdi","sequence":"first","affiliation":[{"name":"Faculty of Fouman College of Engineering University of Tehran Fouman Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3933-9306","authenticated-orcid":false,"given":"Azadeh","family":"Ebrahimian Pirbazari","sequence":"additional","affiliation":[{"name":"Faculty of Fouman College of Engineering University of Tehran Fouman Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fatemeh","family":"Esmaeili Khalilsaraei","sequence":"additional","affiliation":[{"name":"Faculty of Fouman College of Engineering University of Tehran Fouman Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8676-480X","authenticated-orcid":false,"given":"Neda","family":"Asasian Kolur","sequence":"additional","affiliation":[{"name":"Faculty of Fouman College of Engineering University of Tehran Fouman Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0542-581X","authenticated-orcid":false,"given":"Neda","family":"Gilani","sequence":"additional","affiliation":[{"name":"Department of Chemical Engineering University of Guilan Rasht Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2019,11,7]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12274-014-0606-9"},{"key":"e_1_2_6_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/ejic.200801122"},{"key":"e_1_2_6_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cep.2016.08.016"},{"key":"e_1_2_6_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.progsurf.2016.11.001"},{"key":"e_1_2_6_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.apcata.2015.02.013"},{"key":"e_1_2_6_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1872-2067(12)60530-0"},{"key":"e_1_2_6_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jece.2019.103160"},{"key":"e_1_2_6_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10854-017-6683-2"},{"key":"e_1_2_6_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10311-013-0404-8"},{"key":"e_1_2_6_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.apsusc.2015.11.016"},{"key":"e_1_2_6_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jphotochemrev.2015.08.003"},{"key":"e_1_2_6_13_1","doi-asserted-by":"publisher","DOI":"10.1021\/am1010354"},{"key":"e_1_2_6_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jphotochemrev.2017.05.003"},{"issue":"4","key":"e_1_2_6_15_1","first-page":"46","article-title":"Interpreting neural\u2010network connection weights","volume":"6","author":"Garson G. 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