{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T17:54:22Z","timestamp":1770746062067,"version":"3.49.0"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T00:00:00Z","timestamp":1752796800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T00:00:00Z","timestamp":1752796800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"\u56fd\u5bb6\u81ea\u7136\u79d1\u5b66\u57fa\u91d1\u9879\u76ee","award":["62373262"],"award-info":[{"award-number":["62373262"]}]},{"name":"\u56fd\u5bb6\u81ea\u7136\u79d1\u5b66\u57fa\u91d1\u9879\u76ee","award":["62373262"],"award-info":[{"award-number":["62373262"]}]},{"name":"\u56fd\u5bb6\u81ea\u7136\u79d1\u5b66\u57fa\u91d1\u9879\u76ee","award":["62373262"],"award-info":[{"award-number":["62373262"]}]},{"name":"\u56fd\u5bb6\u81ea\u7136\u79d1\u5b66\u57fa\u91d1\u9879\u76ee","award":["62373262"],"award-info":[{"award-number":["62373262"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1007\/s13042-025-02723-9","type":"journal-article","created":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T05:38:24Z","timestamp":1752817104000},"page":"8295-8309","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Dynamic multi-objective optimization control for wastewater treatment process under various operating conditions"],"prefix":"10.1007","volume":"16","author":[{"given":"Xin","family":"Deng","sequence":"first","affiliation":[]},{"given":"Xiaoyu","family":"Xie","sequence":"additional","affiliation":[]},{"given":"Linyu","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Qian","family":"Ning","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,7,18]]},"reference":[{"key":"2723_CR1","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1016\/j.conengprac.2017.09.015","volume":"70","author":"CM Th\u00fcrlimann","year":"2018","unstructured":"Th\u00fcrlimann CM, D\u00fcrrenmatt DJ, Villez K (2018) Soft-sensing with qualitative trend analysis for wastewater treatment plant control. Control Eng Pract 70:121\u2013133","journal-title":"Control Eng Pract"},{"key":"2723_CR2","doi-asserted-by":"publisher","first-page":"116924","DOI":"10.1016\/j.jenvman.2022.116924","volume":"328","author":"H Dai","year":"2023","unstructured":"Dai H et al (2023) Modeling and optimizing of an actual municipal sewage plant: a comparison of diverse multi-objective optimization methods. J Environ Manage 328:116924","journal-title":"J Environ Manage"},{"key":"2723_CR3","doi-asserted-by":"crossref","unstructured":"Da\u00a0Xu L (2020) Industrial information integration\u2013an emerging subject in industrialization and informatization process","DOI":"10.1016\/j.jii.2020.100128"},{"key":"2723_CR4","doi-asserted-by":"publisher","first-page":"133047","DOI":"10.1016\/j.jclepro.2022.133047","volume":"368","author":"CJA Caligan","year":"2022","unstructured":"Caligan CJA, Garcia MMS, Mitra JL, San Juan JLG (2022) Multi-objective optimization for a wastewater treatment plant and sludge-to-energy network. J Clean Prod 368:133047","journal-title":"J Clean Prod"},{"key":"2723_CR5","doi-asserted-by":"publisher","first-page":"101591","DOI":"10.1016\/j.eti.2021.101591","volume":"23","author":"E Tejaswini","year":"2021","unstructured":"Tejaswini E, Panjwani S, Gara UBB, Ambati SR (2021) Multi-objective optimization based controller design for improved wastewater treatment plant operation. Environ Technol Innovation 23:101591","journal-title":"Environ Technol Innovation"},{"key":"2723_CR6","doi-asserted-by":"publisher","first-page":"118227","DOI":"10.1016\/j.jclepro.2019.118227","volume":"240","author":"N Rezaei","year":"2019","unstructured":"Rezaei N, Sierra-Altamiranda A, Diaz-Elsayed N, Charkhgard H, Zhang Q (2019) A multi-objective optimization model for decision support in water reclamation system planning. J Clean Prod 240:118227","journal-title":"J Clean Prod"},{"key":"2723_CR7","doi-asserted-by":"publisher","first-page":"103237","DOI":"10.1016\/j.jwpe.2022.103237","volume":"50","author":"AS Qambar","year":"2022","unstructured":"Qambar AS, Al Khalidy MM (2022) Optimizing dissolved oxygen requirement and energy consumption in wastewater treatment plant aeration tanks using machine learning. J Water Process Eng 50:103237","journal-title":"J Water Process Eng"},{"key":"2723_CR8","doi-asserted-by":"publisher","first-page":"1444","DOI":"10.2166\/wst.2022.281","volume":"86","author":"D Li","year":"2022","unstructured":"Li D, Zou M, Jiang L (2022) Dissolved oxygen control strategies for water treatment: a review. Water Sci Technol 86:1444\u20131466","journal-title":"Water Sci Technol"},{"key":"2723_CR9","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1016\/j.neunet.2021.05.027","volume":"143","author":"D Wang","year":"2021","unstructured":"Wang D, Zhao M, Ha M, Ren J (2021) Neural optimal tracking control of constrained nonaffine systems with a wastewater treatment application. Neural Netw 143:121\u2013132","journal-title":"Neural Netw"},{"key":"2723_CR10","doi-asserted-by":"publisher","first-page":"123233","DOI":"10.1016\/j.jclepro.2020.123233","volume":"274","author":"F Huang","year":"2020","unstructured":"Huang F, Shen W, Zhang X, Seferlis P (2020) Impacts of dissolved oxygen control on different greenhouse gas emission sources in wastewater treatment process. J Clean Prod 274:123233","journal-title":"J Clean Prod"},{"key":"2723_CR11","doi-asserted-by":"publisher","first-page":"100678","DOI":"10.1016\/j.eti.2020.100678","volume":"18","author":"N Khatri","year":"2020","unstructured":"Khatri N, Khatri KK, Sharma A (2020) Enhanced energy saving in wastewater treatment plant using dissolved oxygen control and hydrocyclone. Environ Technol Innov 18:100678","journal-title":"Environ Technol Innov"},{"key":"2723_CR12","doi-asserted-by":"publisher","first-page":"130498","DOI":"10.1016\/j.chemosphere.2021.130498","volume":"279","author":"K Chen","year":"2021","unstructured":"Chen K et al (2021) Optimal control towards sustainable wastewater treatment plants based on multi-agent reinforcement learning. Chemosphere 279:130498","journal-title":"Chemosphere"},{"key":"2723_CR13","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.watres.2014.02.018","volume":"55","author":"C Sweetapple","year":"2014","unstructured":"Sweetapple C, Fu G, Butler D (2014) Multi-objective optimisation of wastewater treatment plant control to reduce greenhouse gas emissions. Water Res 55:52\u201362","journal-title":"Water Res"},{"key":"2723_CR14","doi-asserted-by":"publisher","first-page":"223","DOI":"10.2166\/wst.2015.489","volume":"73","author":"H Dai","year":"2016","unstructured":"Dai H, Chen W, Lu X (2016) The application of multi-objective optimization method for activated sludge process: a review. Water Sci Technol 73:223\u2013235","journal-title":"Water Sci Technol"},{"key":"2723_CR15","doi-asserted-by":"publisher","first-page":"2518","DOI":"10.1109\/TCYB.2019.2925534","volume":"51","author":"H-G Han","year":"2019","unstructured":"Han H-G, Liu Z, Lu W, Hou Y, Qiao J-F (2019) Dynamic mopso-based optimal control for wastewater treatment process. IEEE Trans Cybern 51:2518\u20132528","journal-title":"IEEE Trans Cybern"},{"key":"2723_CR16","doi-asserted-by":"publisher","first-page":"131140","DOI":"10.1016\/j.jclepro.2022.131140","volume":"345","author":"G Niu","year":"2022","unstructured":"Niu G et al (2022) Dynamic optimization of wastewater treatment process based on novel multi-objective ant lion optimization and deep learning algorithm. J Clean Prod 345:131140","journal-title":"J Clean Prod"},{"issue":"2","key":"2723_CR17","doi-asserted-by":"publisher","first-page":"1380","DOI":"10.1109\/TASE.2023.3240497","volume":"21","author":"C Chen","year":"2023","unstructured":"Chen C, Han H, Sun H, Yang H, Qiao J (2023) Multi-objective integrated robust optimal control for wastewater treatment processes. IEEE Trans Autom Sci Eng 21(2):1380\u20131391","journal-title":"IEEE Trans Autom Sci Eng"},{"key":"2723_CR18","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1016\/j.neucom.2017.08.059","volume":"275","author":"J-F Qiao","year":"2018","unstructured":"Qiao J-F, Hou Y, Zhang L, Han H-G (2018) Adaptive fuzzy neural network control of wastewater treatment process with multiobjective operation. Neurocomputing 275:383\u2013393","journal-title":"Neurocomputing"},{"key":"2723_CR19","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1016\/j.compchemeng.2014.03.027","volume":"68","author":"P Vega","year":"2014","unstructured":"Vega P, Revollar S, Francisco M, Mart\u00edn JM (2014) Integration of set point optimization techniques into nonlinear mpc for improving the operation of wwtps. Comput Chem Eng 68:78\u201395","journal-title":"Comput Chem Eng"},{"issue":"3","key":"2723_CR20","doi-asserted-by":"publisher","first-page":"1907","DOI":"10.1109\/TASE.2022.3189048","volume":"20","author":"H-G Han","year":"2022","unstructured":"Han H-G, Zhang L, Qiao J (2022) Dynamic optimal control for wastewater treatment process under multiple operating conditions. IEEE Trans Autom Sci Eng 20(3):1907\u20131919","journal-title":"IEEE Trans Autom Sci Eng"},{"key":"2723_CR21","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1007\/s11157-016-9397-7","volume":"15","author":"J Umamaheswari","year":"2016","unstructured":"Umamaheswari J, Shanthakumar S (2016) Efficacy of microalgae for industrial wastewater treatment: a review on operating conditions, treatment efficiency and biomass productivity. Rev Environ Sci Bio\/technol 15:265\u2013284","journal-title":"Rev Environ Sci Bio\/technol"},{"key":"2723_CR22","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1002\/ep.10295","volume":"27","author":"E Dogan","year":"2008","unstructured":"Dogan E, Ates A, Yilmaz EC, Eren B (2008) Application of artificial neural networks to estimate wastewater treatment plant inlet biochemical oxygen demand. Environ Prog 27:439\u2013446","journal-title":"Environ Prog"},{"key":"2723_CR23","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1016\/j.conengprac.2003.07.001","volume":"12","author":"U Jeppsson","year":"2004","unstructured":"Jeppsson U, Pons M-N (2004) The cost benchmark simulation model\u2013current state and future perspective. Control Eng Pract 12:299\u2013304","journal-title":"Control Eng Pract"},{"key":"2723_CR24","doi-asserted-by":"publisher","first-page":"6925","DOI":"10.1109\/TII.2020.3039272","volume":"17","author":"S Heo","year":"2020","unstructured":"Heo S, Nam K, Loy-Benitez J, Yoo C (2020) Data-driven hybrid model for forecasting wastewater influent loads based on multimodal and ensemble deep learning. IEEE Trans Industr Inf 17:6925\u20136934","journal-title":"IEEE Trans Industr Inf"},{"key":"2723_CR25","doi-asserted-by":"crossref","unstructured":"Hatzakis I, Wallace D (2006) Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach","DOI":"10.1145\/1143997.1144187"},{"key":"2723_CR26","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.watres.2014.01.058","volume":"55","author":"S Ge","year":"2014","unstructured":"Ge S, Peng Y, Qiu S, Zhu A, Ren N (2014) Complete nitrogen removal from municipal wastewater via partial nitrification by appropriately alternating anoxic\/aerobic conditions in a continuous plug-flow step feed process. Water Res 55:95\u2013105","journal-title":"Water Res"},{"key":"2723_CR27","doi-asserted-by":"crossref","unstructured":"Paparrizos J, Gravano L (2015) k-shape: Efficient and accurate clustering of time series","DOI":"10.1145\/2723372.2737793"},{"key":"2723_CR28","doi-asserted-by":"publisher","first-page":"2585","DOI":"10.1109\/TCYB.2014.2311014","volume":"44","author":"Z Deng","year":"2014","unstructured":"Deng Z, Choi K-S, Jiang Y, Wang S (2014) Generalized hidden-mapping ridge regression, knowledge-leveraged inductive transfer learning for neural networks, fuzzy systems and kernel methods. IEEE Trans Cybernet 44:2585\u20132599","journal-title":"IEEE Trans Cybernet"},{"key":"2723_CR29","doi-asserted-by":"publisher","first-page":"1949","DOI":"10.1002\/er.3202","volume":"38","author":"M Sharafi","year":"2014","unstructured":"Sharafi M, ElMekkawy TY (2014) A dynamic mopso algorithm for multiobjective optimal design of hybrid renewable energy systems. Int J Energy Res 38:1949\u20131963","journal-title":"Int J Energy Res"},{"key":"2723_CR30","doi-asserted-by":"publisher","first-page":"2754","DOI":"10.1109\/TCYB.2017.2692385","volume":"47","author":"H Han","year":"2017","unstructured":"Han H, Lu W, Qiao J (2017) An adaptive multiobjective particle swarm optimization based on multiple adaptive methods. IEEE Trans Cybern 47:2754\u20132767","journal-title":"IEEE Trans Cybern"},{"key":"2723_CR31","doi-asserted-by":"crossref","unstructured":"Li Q, Li R, Ji K, Dai W (2015) Kalman filter and its application","DOI":"10.1109\/ICINIS.2015.35"},{"key":"2723_CR32","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1109\/MCS.2006.1580152","volume":"26","author":"Y Li","year":"2006","unstructured":"Li Y, Ang KH, Chong GC (2006) Pid control system analysis and design. IEEE Control Syst Mag 26:32\u201341","journal-title":"IEEE Control Syst Mag"},{"key":"2723_CR33","doi-asserted-by":"publisher","first-page":"105296","DOI":"10.1016\/j.conengprac.2022.105296","volume":"128","author":"H-G Han","year":"2022","unstructured":"Han H-G, Chen C, Sun H-Y, Qiao J-F (2022) Multi-objective integrated optimal control for a wastewater treatment process. Control Eng Pract 128:105296","journal-title":"Control Eng Pract"},{"key":"2723_CR34","unstructured":"Alex J et\u00a0al. Benchmark simulation model no. 1 (bsm1). Report by the IWA Taskgroup on benchmarking of control strategies for WWTPs1 (2008)"},{"key":"2723_CR35","doi-asserted-by":"publisher","first-page":"105274","DOI":"10.1016\/j.jwpe.2024.105274","volume":"61","author":"Q Liu","year":"2024","unstructured":"Liu Q, Jiang X (2024) Dynamic multi-objective optimization control for wastewater treatment process based on modal decomposition and hybrid neural network. J Water Process Eng 61:105274","journal-title":"J Water Process Eng"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-025-02723-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-025-02723-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-025-02723-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T17:01:06Z","timestamp":1760547666000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-025-02723-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,18]]},"references-count":35,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2025,10]]}},"alternative-id":["2723"],"URL":"https:\/\/doi.org\/10.1007\/s13042-025-02723-9","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,18]]},"assertion":[{"value":"27 March 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 June 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 July 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}