{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T00:32:33Z","timestamp":1773793953281,"version":"3.50.1"},"reference-count":37,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,1,28]],"date-time":"2025-01-28T00:00:00Z","timestamp":1738022400000},"content-version":"vor","delay-in-days":27,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100008528","name":"Anyang Institute of Technology","doi-asserted-by":"publisher","award":["SYS202402"],"award-info":[{"award-number":["SYS202402"]}],"id":[{"id":"10.13039\/501100008528","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Electrical and Computer Engineering"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:p>\n                    Kitchen anaerobic wastewater contains a high concentration of insoluble organic matter, and the degradation of organic matter in the wastewater is the key to treating kitchen anaerobic wastewater. The Fenton oxidation process is used to treat kitchen anaerobic wastewater, and the effects of H\n                    <jats:sub>2<\/jats:sub>\n                    O\n                    <jats:sub>2<\/jats:sub>\n                    dosage, Fe\n                    <jats:sup>2+<\/jats:sup>\n                    dosage, reaction time and pH value on chemical oxygen demand (COD) degradation efficiency are explored. The improved particle swarm optimization (IPSO) algorithm is used to optimize the back propagation (BP) neural network, and a prediction model of COD degradation is established based on IPSO\u2010BP neural network. H\n                    <jats:sub>2<\/jats:sub>\n                    O\n                    <jats:sub>2<\/jats:sub>\n                    dosage, Fe\n                    <jats:sup>2+<\/jats:sup>\n                    dosage, reaction time and pH value are selected as the main influencing factors of the COD degradation, and 30 groups of experimental data are selected to train the IPSO\u2010BP neural network. The results predicted by the trained IPSO\u2010BP neural network on 10 groups of test data are compared with the actual values, and the results predicted by BP model and genetic algorithm\u2010BP (GA\u2010BP) model are compared. The IPSO\u2010BP model has the highest fitting accuracy. The root mean square error (RMSE), RMSE coefficient of variation (CV\u2010RMSE), and coefficient of determination (\n                    <jats:italic>R<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    ) were used to evaluate the prediction performance of the model. The indicators of the IPSO\u2010BP model were significantly better than those of the GA\u2010BP model and the BP model, indicating that IPSO\u2010BP model had better generalization ability and could predict COD concentration more effectively. The optimal conditions for Fenton oxidation obtained from IPSO\u2010BP model are as follows: the dosage of H\n                    <jats:sub>2<\/jats:sub>\n                    O\n                    <jats:sub>2<\/jats:sub>\n                    is 2000\u2009mg\/L, the dosage of Fe\n                    <jats:sup>2+<\/jats:sup>\n                    is 1200\u2009mg\/L, the pH value is 2.8, the reaction time is 75\u2009min, and the COD removal rate is 80.125%, which is consistent with the experimental results. Through gas chromatography\u2010mass spectrometry (GC\u2010MS) analysis, most organic compounds in kitchen anaerobic wastewater are oxidized and decomposed, indicating that the IPSO\u2010BP model has good predictive quality.\n                  <\/jats:p>","DOI":"10.1155\/jece\/3213686","type":"journal-article","created":{"date-parts":[[2025,1,28]],"date-time":"2025-01-28T07:50:02Z","timestamp":1738050602000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Prediction of COD Degradation in Fenton Oxidation Treatment of Kitchen Anaerobic Wastewater Based on IPSO\u2010BP Neural Network"],"prefix":"10.1155","volume":"2025","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4984-2594","authenticated-orcid":false,"given":"Tianpeng","family":"Zhang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0008-3513-2392","authenticated-orcid":false,"given":"Pengfei","family":"Ji","sequence":"additional","affiliation":[]},{"given":"Dayong","family":"Tian","sequence":"additional","affiliation":[]},{"given":"Rui","family":"Xu","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2025,1,28]]},"reference":[{"key":"e_1_2_10_1_2","first-page":"3728","article-title":"Performance of an Anaerobic Membrane Bioreactor Treating High Concentration Kitchen Wastewater","volume":"16","author":"Xiao W.","year":"2022","journal-title":"Chinese Journal of Environmental Engineering"},{"key":"e_1_2_10_2_2","first-page":"1","article-title":"Pretreatment of Kitchen Waste Wastewater and Recovery of Soluble Carbon Source by Fermentation","volume":"37","author":"shuizhou K.","year":"2021","journal-title":"China Water and Wastewater"},{"key":"e_1_2_10_3_2","volume-title":"Study of Influence Factors and Mechanisms of Anaerobic Digestion of Food Wastewater to Produce Hydrogen and Acids","author":"Huang J.","year":"2021"},{"key":"e_1_2_10_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.iot.2024.101255"},{"key":"e_1_2_10_5_2","first-page":"145","article-title":"Pilot-Scale Study on Advanced Treatment of Industrial Wastewater Tail Water by Fenton Oxidation Process","volume":"49","author":"Zhang Q.","year":"2022","journal-title":"Guangdong Chemical Industry"},{"key":"e_1_2_10_6_2","first-page":"60","article-title":"Research Progress of Coking Wastewater Treatment by Fenton Oxidation Process","volume":"54","author":"Han Y.","year":"2023","journal-title":"Fuel and Chemical Processes"},{"key":"e_1_2_10_7_2","doi-asserted-by":"publisher","DOI":"10.1007\/s40097-021-00409-6"},{"key":"e_1_2_10_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.psep.2021.09.029"},{"key":"e_1_2_10_9_2","first-page":"49","article-title":"Treatment of Reused Petrochemical Wastewater by Ternary Microelectrolysis-Fenton Oxidation Process","author":"Yang R.","year":"2012","journal-title":"Industrial Water Treatment"},{"key":"e_1_2_10_10_2","first-page":"66","article-title":"Oxidation Mechanism and Research Progress of Fenton Reagent in the Treatment of Industrial Wastewater Containing Refractory Organic Pollution","volume":"31","author":"Zhang L.","year":"2010","journal-title":"Journal of Shaoguan University"},{"key":"e_1_2_10_11_2","first-page":"1805","article-title":"Study on Further Treatment of Chemical Wastewater With Fenton Method","author":"Zhang Y.","year":"2015","journal-title":"Contemporary Chemical Industry"},{"key":"e_1_2_10_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jece.2015.12.016"},{"key":"e_1_2_10_13_2","first-page":"1","article-title":"Removal of Organic Pollutants From Industrial Wastewater by Applying Photo-Fenton Oxidation Technology","volume":"35","author":"Ebrahiem E. 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