{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T02:47:40Z","timestamp":1780541260937,"version":"3.54.1"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"19","license":[{"start":{"date-parts":[[2023,3,7]],"date-time":"2023-03-07T00:00:00Z","timestamp":1678147200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,3,7]],"date-time":"2023-03-07T00:00:00Z","timestamp":1678147200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Environ Sci Pollut Res"],"DOI":"10.1007\/s11356-023-26282-0","type":"journal-article","created":{"date-parts":[[2023,3,7]],"date-time":"2023-03-07T18:02:58Z","timestamp":1678212178000},"page":"54835-54845","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Evaluation of adaptive neuro-fuzzy inference system-genetic algorithm in the prediction and optimization of NOx emission in cement precalcining kiln"],"prefix":"10.1007","volume":"30","author":[{"given":"Anthony I.","family":"Okoji","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ambrose N.","family":"Anozie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James A.","family":"Omoleye","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6136-4439","authenticated-orcid":false,"given":"Abiola E.","family":"Taiwo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Damilola E.","family":"Babatunde","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,3,7]]},"reference":[{"key":"26282_CR1","first-page":"111","volume":"8","author":"MZ Alam","year":"2018","unstructured":"Alam MZ, Armin E, Haque M, Kayesh JHE, Qayum A (2018) Air pollutants and their possible health effects at different locations in Dhaka City. J Curr Chem Pharm Sci 8:111","journal-title":"J Curr Chem Pharm Sci"},{"key":"26282_CR2","doi-asserted-by":"publisher","unstructured":"Arsie I, D'Aniello F, Pianese C, De Cesare M, Paiano L (2018) Development and experimental validation of a control oriented model of scr for automotive application. SAE International United States Technical Paper, 2018\u201301-1263.\u00a0https:\/\/doi.org\/10.4271\/2018-01-1263","DOI":"10.4271\/2018-01-1263"},{"key":"26282_CR3","unstructured":"Bolaji BO, Adejuyigbe SB (2006) Vehicle emissions and their effects on the natural environment. JGIE4:35\u201340"},{"key":"26282_CR4","first-page":"788","volume":"64","author":"P Cao","year":"2013","unstructured":"Cao P, Luo X (2013) Modeling of soft sensor for chemical process. Ciesc J 64:788\u2013800","journal-title":"Ciesc J"},{"key":"26282_CR5","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.apcata.2018.03.012","volume":"557","author":"L Cao","year":"2018","unstructured":"Cao L, Chen L, Wu X, Ran R, Xu T, Chen Z, Weng D (2018) TRA and DRIFTS studies of the fast SCR reaction over CeO2\/TiO2 catalyst at low temperatures. Appl Catal A: Gen 557:46\u201354","journal-title":"Appl Catal A: Gen"},{"key":"26282_CR6","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1080\/10937404.2014.946164","volume":"17","author":"S Costa","year":"2014","unstructured":"Costa S, Ferreira J, Silveira C, Costa C, Lopes D, Relvas H, Borrego C, Roebeling P, Miranda AI, Paulo Teixeira J (2014) Integrating health on air quality assessment\u2014review report on health risks of two major European outdoor air pollutants: PM and NO2. J Toxicol Environ Health Part B 17:307\u2013340","journal-title":"J Toxicol Environ Health Part B"},{"key":"26282_CR7","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1016\/j.apenergy.2011.12.039","volume":"97","author":"R Dong","year":"2012","unstructured":"Dong R, Lu H, Yu Y, Zhang Z (2012) A feasible process for simultaneous removal of CO2, SO2 and NOx in the cement industry by NH3 scrubbing. Appl Energy 97:185\u2013191","journal-title":"Appl Energy"},{"key":"26282_CR8","doi-asserted-by":"publisher","first-page":"20190327","DOI":"10.1098\/rsta.2019.0327","volume":"378","author":"L Emberson","year":"2020","unstructured":"Emberson L (2020) Effects of ozone on agriculture, forests and grasslands. Phil Trans R Soc A 378:20190327","journal-title":"Phil Trans R Soc A"},{"key":"26282_CR9","doi-asserted-by":"publisher","first-page":"1979","DOI":"10.1016\/j.atmosenv.2011.01.022","volume":"45","author":"Y Feng","year":"2011","unstructured":"Feng Y, Zhang W, Sun D, Zhang L (2011) Ozone concentration forecast method based on genetic algorithm optimized back propagation neural networks and support vector machine data classification. Atmos Environ 45:1979\u20131985","journal-title":"Atmos Environ"},{"key":"26282_CR10","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1007\/s11869-018-0630-0","volume":"12","author":"A Ghasemi","year":"2019","unstructured":"Ghasemi A, Amanollahi J (2019) Integration of ANFIS model and forward selection method for air quality forecasting. Air Qual Atmos Health 12:59\u201372","journal-title":"Air Qual Atmos Health"},{"key":"26282_CR11","doi-asserted-by":"publisher","first-page":"136712","DOI":"10.1016\/j.scitotenv.2020.136712","volume":"714","author":"F Gholami","year":"2020","unstructured":"Gholami F, Tomas M, Gholami Z, Vakili M (2020) Technologies for the nitrogen oxides reduction from flue gas: A review. Sci Total Environ 714:136712","journal-title":"Sci Total Environ"},{"key":"26282_CR12","doi-asserted-by":"publisher","first-page":"1059","DOI":"10.3390\/su10041059","volume":"10","author":"A HadiAbdulwahid","year":"2018","unstructured":"HadiAbdulwahid A, Wang S (2018) A novel method of protection to prevent reverse power flow based on neuro-fuzzy networks for smart grid. Sustainability 10:1059","journal-title":"Sustainability"},{"key":"26282_CR13","unstructured":"Hansen TK (2017) Development of new diesel oxidation and NH3 slip catalysts. Ph.D. Thesis, Technical University of Denmark (DTU), Lyngby, Denmark"},{"key":"26282_CR14","doi-asserted-by":"publisher","first-page":"106904","DOI":"10.1016\/j.asoc.2020.106904","volume":"99","author":"H Harandizadeh","year":"2021","unstructured":"Harandizadeh H, Armaghani DJ (2021) Prediction of air-overpressure induced by blasting using an ANFIS-PNN model optimized by GA. Appl Soft Comput 99:106904","journal-title":"Appl Soft Comput"},{"key":"26282_CR15","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1016\/j.materresbull.2018.04.009","volume":"104","author":"G Hu","year":"2018","unstructured":"Hu G, Yang J, Tian Y, Kong B, Liu Q, Ren S, Li J, Kong M (2018) Effect of Ce doping on the resistance of Na over V2O5-WO3\/TiO2 SCR catalysts. Mater Res Bull 104:112\u2013118","journal-title":"Mater Res Bull"},{"key":"26282_CR16","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1007\/s10098-012-0490-5","volume":"15","author":"P Ilamathi","year":"2013","unstructured":"Ilamathi P, Selladurai V, Balamurugan K, Sathyanathan V (2013) ANN\u2013GA approach for predictive modeling and optimization of NOx emission in a tangentially fired boiler. Clean Technol Environ Policy 15:125\u2013131","journal-title":"Clean Technol Environ Policy"},{"key":"26282_CR17","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1016\/j.ijrmms.2004.03.095","volume":"41","author":"Y-H Jong","year":"2004","unstructured":"Jong Y-H, Lee C-I (2004) Influence of geological conditions on the powder factor for tunnel blasting. Int J Rock Mech Min Sci 41:533\u2013538","journal-title":"Int J Rock Mech Min Sci"},{"key":"26282_CR18","doi-asserted-by":"publisher","first-page":"2276","DOI":"10.1109\/TSG.2016.2609740","volume":"9","author":"K Kampouropoulos","year":"2016","unstructured":"Kampouropoulos K, Andrade F, Sala E, Espinosa AG, Romeral L (2016) Multiobjective optimization of multi-carrier energy system using a combination of ANFIS and genetic algorithms. IEEE Trans Smart Grid 9:2276\u20132283","journal-title":"IEEE Trans Smart Grid"},{"key":"26282_CR19","doi-asserted-by":"publisher","first-page":"1115","DOI":"10.1016\/j.envpol.2018.05.072","volume":"241","author":"Y Li","year":"2018","unstructured":"Li Y, Jiang P, She Q, Lin G (2018) Research on air pollutant concentration prediction method based on self-adaptive neuro-fuzzy weighted extreme learning machine. Environ Pollut 241:1115\u20131127","journal-title":"Environ Pollut"},{"key":"26282_CR20","doi-asserted-by":"crossref","unstructured":"Li Z, Liu XM, Yang DH, Qin WJ, Yang GS, Zhang DL (2014) Research of the SNCR Process and its Application. Adv Mat Res\u00a0953:1307\u20131314","DOI":"10.4028\/www.scientific.net\/AMR.953-954.1307"},{"key":"26282_CR21","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1016\/j.joei.2014.04.004","volume":"88","author":"Z Liu","year":"2015","unstructured":"Liu Z, Wang Z, Yuan M, Yu H (2015) Thermal efficiency modelling of the cement clinker manufacturing process. J Energy Inst 88:76\u201386","journal-title":"J Energy Inst"},{"key":"26282_CR22","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1016\/j.energy.2013.02.062","volume":"55","author":"Y Lv","year":"2013","unstructured":"Lv Y, Liu J, Yang T, Zeng D (2013) A novel least squares support vector machine ensemble model for NOx emission prediction of a coal-fired boiler. Energy 55:319\u2013329","journal-title":"Energy"},{"key":"26282_CR23","first-page":"62","volume":"19","author":"J Mao","year":"2011","unstructured":"Mao J, Zhao H-D, Yao J-J (2011) Application and prospect of artificial neural network [J]. Electron Des Eng 19:62\u201365","journal-title":"Electron Des Eng"},{"key":"26282_CR24","first-page":"1044","volume":"7","author":"SS Mehraj","year":"2013","unstructured":"Mehraj SS, Bhat G, Balkhi HM, Gul T (2013) Health risks for population living in the neighborhood of a cement factory. Afr J Environ Sci Technol 7:1044\u20131052","journal-title":"Afr J Environ Sci Technol"},{"key":"26282_CR25","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1016\/j.rser.2016.05.065","volume":"63","author":"K Mohammadi","year":"2016","unstructured":"Mohammadi K, Shamshirband S, Kamsin A, Lai P, Mansor Z (2016) Identifying the most significant input parameters for predicting global solar radiation using an ANFIS selection procedure. Renew Sustain Energy Rev 63:423\u2013434","journal-title":"Renew Sustain Energy Rev"},{"key":"26282_CR26","doi-asserted-by":"publisher","first-page":"934","DOI":"10.1080\/00207233.2012.732751","volume":"69","author":"O Oguntoke","year":"2012","unstructured":"Oguntoke O, Awanu AE, Annegarn HJ (2012) Impact of cement factory operations on air quality and human health in Ewekoro Local Government Area, South-Western Nigeria. Int J Environ Stud 69:934\u2013945","journal-title":"Int J Environ Stud"},{"key":"26282_CR27","doi-asserted-by":"publisher","first-page":"1930493","DOI":"10.1080\/23311916.2021.1930493","volume":"8","author":"AI Okoji","year":"2021","unstructured":"Okoji AI, Anozie AN, Omoleye JA (2021) Evaluation of optimization techniques for predicting exergy efficiency of the cement raw meal production process. Cogent Eng 8:1930493","journal-title":"Cogent Eng"},{"key":"26282_CR28","doi-asserted-by":"publisher","first-page":"101704","DOI":"10.1016\/j.asej.2022.101704","volume":"13","author":"AI Okoji","year":"2022","unstructured":"Okoji AI, Anozie AN, Omoleye JA (2022) Evaluating the thermodynamic efficiency of the cement grate clinker cooler process using artificial neural networks and ANFIS. Ain Shams Eng J 13:101704","journal-title":"Ain Shams Eng J"},{"key":"26282_CR29","doi-asserted-by":"publisher","first-page":"5097","DOI":"10.1016\/j.aej.2021.10.010","volume":"61","author":"AI Okoji","year":"2022","unstructured":"Okoji AI, Anozie AN, Omoleye JA, Taiwo AE, Osuolale FN (2022) Energetic assessment of a precalcining rotary kiln in a cement plant using process simulator and neural networks. Alex Eng J 61:5097\u20135109","journal-title":"Alex Eng J"},{"key":"26282_CR30","doi-asserted-by":"publisher","first-page":"103794","DOI":"10.1016\/j.arabjc.2022.103794","volume":"15","author":"CN Okoji","year":"2022","unstructured":"Okoji CN, Okoji AI, Ibrahim MS, Obinna O (2022) Comparative analysis of adaptive neuro-fuzzy inference system (ANFIS) and RSRM models to predict DBP (trihalomethanes) levels in the water treatment plant. Arab J Chem 15:103794","journal-title":"Arab J Chem"},{"key":"26282_CR31","doi-asserted-by":"publisher","first-page":"704","DOI":"10.1016\/j.joei.2017.05.010","volume":"91","author":"V Praveena","year":"2018","unstructured":"Praveena V, Martin MLJ (2018) A review on various after treatment techniques to reduce NOx emissions in a CI engine. J Energy Inst 91:704\u2013720","journal-title":"J Energy Inst"},{"key":"26282_CR32","doi-asserted-by":"crossref","unstructured":"Qiuyun S, Zhugang Y (2014) Working Condition recognition of cement decomposition furnace based on art-2 neural network. In:\u00a02014 Sixth International Conference on Measuring Technology and Mechatronics Automation, Zhangjiajie, China,  IEEE, pp 807\u2013812","DOI":"10.1109\/ICMTMA.2014.203"},{"key":"26282_CR33","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1016\/j.enconman.2016.02.017","volume":"114","author":"H Shahin","year":"2016","unstructured":"Shahin H, Hassanpour S, Saboonchi A (2016) Thermal energy analysis of a lime production process: Rotary kiln, preheater and cooler. Energy Convers Manage 114:110\u2013121","journal-title":"Energy Convers Manage"},{"key":"26282_CR34","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.conengprac.2010.08.004","volume":"19","author":"KS Stadler","year":"2011","unstructured":"Stadler KS, Poland J, Gallestey E (2011) Model predictive control of a rotary cement kiln. Control Eng Pract 19:1\u20139","journal-title":"Control Eng Pract"},{"key":"26282_CR35","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.jtice.2019.02.020","volume":"99","author":"L Tan","year":"2019","unstructured":"Tan L, Guo Y, Liu Z, Feng P, Li Z (2019) An investigation on the catalytic characteristic of NOx reduction in SCR systems. J Taiwan Inst Chem Eng 99:53\u201359","journal-title":"J Taiwan Inst Chem Eng"},{"key":"26282_CR36","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1016\/j.energy.2018.01.003","volume":"153","author":"C Wang","year":"2018","unstructured":"Wang C, Liu Y, Zheng S, Jiang A (2018) Optimizing combustion of coal fired boilers for reducing NOx emission using Gaussian Process. Energy 153:149\u2013158","journal-title":"Energy"},{"key":"26282_CR37","doi-asserted-by":"publisher","first-page":"122669","DOI":"10.1016\/j.jclepro.2020.122669","volume":"272","author":"H Wu","year":"2020","unstructured":"Wu H, Cai J, Ren Q, Xu J, Chu F, Lyu Q (2020) An efficient and economic denitration technology based on fuel pretreatment for cement cleaner production. J Clean Prod 272:122669","journal-title":"J Clean Prod"},{"key":"26282_CR38","first-page":"423","volume":"38","author":"J Xiuzhang","year":"2018","unstructured":"Xiuzhang J, Shaokang Z (2018) Prediction of denitrification system inlet nitrogen oxide based on neural network online learning. J Hebei Univ (Natural Science Edition) 38:423","journal-title":"J Hebei Univ (Natural Science Edition)"},{"key":"26282_CR39","doi-asserted-by":"publisher","first-page":"1104","DOI":"10.3390\/pr8091104","volume":"8","author":"Y Yao","year":"2020","unstructured":"Yao Y, Chen Y (2020) Technical Route to Achieve Ultra-Low Emission of Nitrogen Oxides with Predictive Model of Nitrogen Oxide Background Concentration. Processes 8:1104","journal-title":"Processes"},{"key":"26282_CR40","doi-asserted-by":"publisher","first-page":"657","DOI":"10.1109\/TIE.2014.2308133","volume":"62","author":"S Yin","year":"2014","unstructured":"Yin S, Li X, Gao H, Kaynak O (2014) Data-based techniques focused on modern industry: An overview. IEEE Trans Industr Electron 62:657\u2013667","journal-title":"IEEE Trans Industr Electron"},{"key":"26282_CR41","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1080\/00207233.2017.1280322","volume":"74","author":"Y Zhang","year":"2017","unstructured":"Zhang Y, Wang W, Shao S, Duan S, Hou H (2017) ANN-GA approach for predictive modelling and optimization of NOx emissions in a cement precalcining kiln. Int J Environ Stud 74:253\u2013261","journal-title":"Int J Environ Stud"},{"key":"26282_CR42","doi-asserted-by":"publisher","first-page":"4987","DOI":"10.1021\/acs.iecr.9b05207","volume":"59","author":"J Zheng","year":"2020","unstructured":"Zheng J, Du W, Lang Z, Qian F (2020) Modeling and Optimization of the Cement Calcination Process for Reducing NO x Emission Using an Improved Just-In-Time Gaussian Mixture Regression. Ind Eng Chem Res 59:4987\u20134999","journal-title":"Ind Eng Chem Res"}],"container-title":["Environmental Science and Pollution Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11356-023-26282-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11356-023-26282-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11356-023-26282-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,21]],"date-time":"2023-04-21T05:42:25Z","timestamp":1682055745000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11356-023-26282-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,7]]},"references-count":42,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["26282"],"URL":"https:\/\/doi.org\/10.1007\/s11356-023-26282-0","relation":{},"ISSN":["1614-7499"],"issn-type":[{"value":"1614-7499","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,7]]},"assertion":[{"value":"22 September 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 February 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 March 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"Informed consent was obtained from all individual participants included in the study.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}