{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T13:18:21Z","timestamp":1777641501598,"version":"3.51.4"},"reference-count":92,"publisher":"Springer Science and Business Media LLC","issue":"16","license":[{"start":{"date-parts":[[2023,4,6]],"date-time":"2023-04-06T00:00:00Z","timestamp":1680739200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,4,6]],"date-time":"2023-04-06T00:00:00Z","timestamp":1680739200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"New York State Empire State Development","award":["134146"],"award-info":[{"award-number":["134146"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2023,6]]},"DOI":"10.1007\/s00521-023-08497-x","type":"journal-article","created":{"date-parts":[[2023,4,6]],"date-time":"2023-04-06T12:04:27Z","timestamp":1680782667000},"page":"11611-11623","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":41,"title":["Data-driven approaches and model-based methods for detecting and locating leaks in water distribution systems: a literature review"],"prefix":"10.1007","volume":"35","author":[{"given":"Waid","family":"Nimri","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1829-3836","authenticated-orcid":false,"given":"Yong","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Ziang","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Chengbin","family":"Deng","sequence":"additional","affiliation":[]},{"given":"Kristofor","family":"Sellstrom","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,4,6]]},"reference":[{"key":"8497_CR1","unstructured":"Liemberger R, Marin P (2006) The challenge of reducing non-revenue water in developing countries\u2014how the private sector can help: a look at performance-based service contracting"},{"issue":"3","key":"8497_CR2","doi-asserted-by":"crossref","first-page":"831","DOI":"10.2166\/ws.2018.129","volume":"19","author":"R Liemberger","year":"2019","unstructured":"Liemberger R, Wyatt A (2019) Quantifying the global non-revenue water problem. Water Supply 19(3):831\u2013837","journal-title":"Water Supply"},{"issue":"8","key":"8497_CR3","doi-asserted-by":"crossref","first-page":"6374","DOI":"10.1109\/TIE.2018.2874583","volume":"66","author":"J Xu","year":"2018","unstructured":"Xu J, Chai KTC, Wu G, Han B, Wai ELC, Li W, Gu Y (2018) Low-cost, tiny-sized MEMS hydrophone sensor for water pipeline leak detection. IEEE Trans Ind Electron 66(8):6374\u20136382","journal-title":"IEEE Trans Ind Electron"},{"key":"8497_CR4","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.jclepro.2013.05.018","volume":"54","author":"TC Britton","year":"2013","unstructured":"Britton TC, Stewart RA, O\u2019Halloran KR (2013) Smart metering: enabler for rapid and effective post meter leakage identification and water loss management. J Clean Prod 54:166\u2013176","journal-title":"J Clean Prod"},{"issue":"16","key":"8497_CR5","doi-asserted-by":"crossref","first-page":"9262","DOI":"10.3390\/su13169262","volume":"13","author":"CW Lee","year":"2021","unstructured":"Lee CW, Yoo DG (2021) Development of leakage detection model and its application for water distribution networks using RNN-LSTM. Sustainability 13(16):9262","journal-title":"Sustainability"},{"issue":"5","key":"8497_CR6","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1002\/j.1551-8833.2003.tb10368.x","volume":"95","author":"MR Karim","year":"2003","unstructured":"Karim MR, Abbaszadegan M, LeChevallier M (2003) Potential for pathogen intrusion during pressure transients. J Am Water Works Ass 95(5):134\u2013146","journal-title":"J Am Water Works Ass"},{"issue":"1","key":"8497_CR7","doi-asserted-by":"crossref","first-page":"04015036","DOI":"10.1061\/(ASCE)HY.1943-7900.0001040","volume":"142","author":"S Fox","year":"2016","unstructured":"Fox S, Shepherd W, Collins R, Boxall J (2016) Experimental quantification of contaminant ingress into a buried leaking pipe during transient events. J Hydraul Eng 142(1):04015036","journal-title":"J Hydraul Eng"},{"issue":"9","key":"8497_CR8","doi-asserted-by":"crossref","first-page":"972","DOI":"10.1080\/1573062X.2017.1279191","volume":"14","author":"Y Wu","year":"2017","unstructured":"Wu Y, Liu S (2017) A review of data-driven approaches for burst detection in water distribution systems. Urban Water J 14(9):972\u2013983","journal-title":"Urban Water J"},{"key":"8497_CR9","unstructured":"Wang XJ, Simpson AR, Lambert MF, V\u00edtkovsk\u00fd JP (2001) Leak detection in pipeline systems using hydraulic methods: a review. In: Conference on hydraulics in civil engineering, the institution of engineers, Australia, Hobart (pp. 23\u201330)"},{"issue":"2","key":"8497_CR10","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1111\/j.1747-6593.1994.tb00913.x","volume":"8","author":"A Lambert","year":"1994","unstructured":"Lambert A (1994) Accounting for losses: the bursts and background concept. Water Environ J 8(2):205\u2013214","journal-title":"Water Environ J"},{"issue":"15","key":"8497_CR11","doi-asserted-by":"crossref","first-page":"4821","DOI":"10.1007\/s11269-017-1780-9","volume":"31","author":"E Farah","year":"2017","unstructured":"Farah E, Shahrour I (2017) Leakage detection using smart water system: combination of water balance and automated minimum night flow. Water Resour Manage 31(15):4821\u20134833","journal-title":"Water Resour Manage"},{"issue":"3","key":"8497_CR12","doi-asserted-by":"crossref","first-page":"617","DOI":"10.2166\/hydro.2013.057","volume":"16","author":"SR Mounce","year":"2014","unstructured":"Mounce SR, Mounce RB, Jackson T, Austin J, Boxall JB (2014) Pattern matching and associative artificial neural networks for water distribution system time series data analysis. J Hydroinf 16(3):617\u2013632","journal-title":"J Hydroinf"},{"key":"8497_CR13","unstructured":"Loveday M, Dixon J (2005) DMA sustainability in developing countries. In: Proceedings. IWA Specialized Conference: Leakage"},{"issue":"2","key":"8497_CR14","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1061\/(ASCE)WR.1943-5452.0000245","volume":"139","author":"HE Mutikanga","year":"2013","unstructured":"Mutikanga HE, Sharma SK, Vairavamoorthy K (2013) Methods and tools for managing losses in water distribution systems. J Water Resour Plan Manag 139(2):166\u2013174","journal-title":"J Water Resour Plan Manag"},{"key":"8497_CR15","doi-asserted-by":"crossref","first-page":"104264","DOI":"10.1016\/j.engfailanal.2019.104264","volume":"109","author":"D Zaman","year":"2020","unstructured":"Zaman D, Tiwari MK, Gupta AK, Sen D (2020) A review of leakage detection strategies for pressurized pipeline in steady-state. Eng Fail Anal 109:104264","journal-title":"Eng Fail Anal"},{"issue":"7","key":"8497_CR16","doi-asserted-by":"crossref","first-page":"e16532","DOI":"10.1002\/aic.16532","volume":"65","author":"J Xie","year":"2019","unstructured":"Xie J, Xu X, Dubljevic S (2019) Long range pipeline leak detection and localization using discrete observer and support vector machine. AIChE J 65(7):e16532","journal-title":"AIChE J"},{"issue":"5","key":"8497_CR17","doi-asserted-by":"crossref","first-page":"512","DOI":"10.2166\/aqua.2020.022","volume":"69","author":"Z Xue","year":"2020","unstructured":"Xue Z, Tao L, Fuchun J, Riehle E, Xiang H, Bowen N, Singh RP (2020) Application of acoustic intelligent leak detection in an urban water supply pipe network. J Water Supply Res Technol AQUA 69(5):512\u2013520","journal-title":"J Water Supply Res Technol AQUA"},{"issue":"3","key":"8497_CR18","doi-asserted-by":"crossref","first-page":"429","DOI":"10.2166\/ws.2014.131","volume":"15","author":"R Li","year":"2015","unstructured":"Li R, Huang H, Xin K, Tao T (2015) A review of methods for burst\/leakage detection and location in water distribution systems. Water Sci Technol Water Supply 15(3):429\u2013441","journal-title":"Water Sci Technol Water Supply"},{"issue":"4","key":"8497_CR19","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/j.jher.2009.02.003","volume":"2","author":"AF Colombo","year":"2009","unstructured":"Colombo AF, Lee P, Karney BW (2009) A selective literature review of transient-based leak detection methods. J Hydro Environ Res 2(4):212\u2013227","journal-title":"J Hydro Environ Res"},{"issue":"7","key":"8497_CR20","doi-asserted-by":"crossref","first-page":"3282","DOI":"10.2166\/ws.2021.101","volume":"21","author":"Z Hu","year":"2021","unstructured":"Hu Z, Chen B, Chen W, Tan D, Shen D (2021) Review of model-based and data-driven approaches for leak detection and location in water distribution systems. Water Supply 21(7):3282\u20133306","journal-title":"Water Supply"},{"key":"8497_CR21","doi-asserted-by":"crossref","unstructured":"Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group* (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med 151(4): 264-269","DOI":"10.7326\/0003-4819-151-4-200908180-00135"},{"issue":"4\u20135","key":"8497_CR22","doi-asserted-by":"crossref","first-page":"237","DOI":"10.2166\/wst.2002.0595","volume":"45","author":"SR Mounce","year":"2002","unstructured":"Mounce SR, Day AJ, Wood AS, Khan A, Widdop PD, Machell J (2002) A neural network approach to burst detection. Water Sci Technol 45(4\u20135):237\u2013246","journal-title":"Water Sci Technol"},{"issue":"1","key":"8497_CR23","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1080\/15730620600578538","volume":"3","author":"SR Mounce","year":"2006","unstructured":"Mounce SR, Machell J (2006) Burst detection using hydraulic data from water distribution systems with artificial neural networks. Urban Water Journal 3(1):21\u201331","journal-title":"Urban Water Journal"},{"key":"8497_CR24","unstructured":"Mounce SR, Boxall JB, Machell J (2007) An artificial neural network\/fuzzy logic system for DMA flow meter data analysis providing burst identification and size estimation. Water management challenges in global change, pp  313\u2013320"},{"issue":"4","key":"8497_CR25","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1080\/15730620802673079","volume":"6","author":"K Aksela","year":"2009","unstructured":"Aksela K, Aksela M, Vahala R (2009) Leakage detection in a real distribution network using a SOM. Urban Water J 6(4):279\u2013289","journal-title":"Urban Water J"},{"issue":"3","key":"8497_CR26","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1061\/(ASCE)WR.1943-5452.0000030","volume":"136","author":"SR Mounce","year":"2010","unstructured":"Mounce SR, Boxall JB, Machell J (2010) Development and verification of an online artificial intelligence system for detection of bursts and other abnormal flows. J Water Resour Plan Manag 136(3):309\u2013318","journal-title":"J Water Resour Plan Manag"},{"issue":"4","key":"8497_CR27","doi-asserted-by":"crossref","first-page":"672","DOI":"10.2166\/hydro.2010.144","volume":"13","author":"SR Mounce","year":"2011","unstructured":"Mounce SR, Mounce RB, Boxall JB (2011) Novelty detection for time series data analysis in water distribution systems using support vector machines. J Hydroinf 13(4):672\u2013686","journal-title":"J Hydroinf"},{"key":"8497_CR28","doi-asserted-by":"crossref","unstructured":"Nasir MT, Mysorewala M, Cheded L, Siddiqui B, Sabih M (2014) Measurement error sensitivity analysis for detecting and locating leak in pipeline using ANN and SVM. In: 2014 IEEE 11th international multi-conference on systems, signals and devices (SSD14), IEEE, (pp. 1\u20134)","DOI":"10.1109\/SSD.2014.6808847"},{"issue":"3","key":"8497_CR29","doi-asserted-by":"crossref","first-page":"634","DOI":"10.2166\/hydro.2013.094","volume":"15","author":"M Romano","year":"2013","unstructured":"Romano M, Kapelan Z, Savi\u0107 DA (2013) Geostatistical techniques for approximate location of pipe burst events in water distribution systems. J Hydroinf 15(3):634\u2013651","journal-title":"J Hydroinf"},{"issue":"1","key":"8497_CR30","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1061\/(ASCE)PS.1949-1204.0000070","volume":"2","author":"G Ye","year":"2011","unstructured":"Ye G, Fenner RA (2011) Kalman filtering of hydraulic measurements for burst detection in water distribution systems. J Pipeline Syst Eng Pract 2(1):14\u201322","journal-title":"J Pipeline Syst Eng Pract"},{"issue":"1","key":"8497_CR31","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1061\/(ASCE)WR.1943-5452.0000147","volume":"138","author":"CV Palau Estevan","year":"2012","unstructured":"Palau Estevan CV, Arregui de la Cruz F, Carlos Alberola MDM (2012) Burst detection in water networks using principal component analysis. J Water Resour Plan Manag 138(1):47\u201354","journal-title":"J Water Resour Plan Manag"},{"issue":"4","key":"8497_CR32","doi-asserted-by":"crossref","first-page":"992","DOI":"10.2166\/hydro.2012.109","volume":"14","author":"DG Eliades","year":"2012","unstructured":"Eliades DG, Polycarpou MM (2012) Leakage fault detection in district metered areas of water distribution systems. J Hydroinf 14(4):992\u20131005","journal-title":"J Hydroinf"},{"issue":"4","key":"8497_CR33","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1061\/(ASCE)WR.1943-5452.0000344","volume":"140","author":"G Ye","year":"2014","unstructured":"Ye G, Fenner RA (2014) Weighted least squares with expectation-maximization algorithm for burst detection in UK water distribution systems. J Water Resour Plan Manag 140(4):417\u2013424","journal-title":"J Water Resour Plan Manag"},{"issue":"5","key":"8497_CR34","doi-asserted-by":"crossref","first-page":"1194","DOI":"10.2166\/hydro.2014.120","volume":"16","author":"M Bakker","year":"2014","unstructured":"Bakker M, Vreeburg JHG, Van De Roer M, Rietveld LC (2014) Heuristic burst detection method using flow and pressure measurements. J Hydroinf 16(5):1194\u20131209","journal-title":"J Hydroinf"},{"key":"8497_CR35","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.proeng.2015.08.847","volume":"119","author":"C Hutton","year":"2015","unstructured":"Hutton C, Kapelan Z (2015) Real-time burst detection in water distribution systems using a Bayesian demand forecasting methodology. Procedia Eng 119:13\u201318","journal-title":"Procedia Eng"},{"issue":"5","key":"8497_CR36","doi-asserted-by":"crossref","first-page":"04014070","DOI":"10.1061\/(ASCE)WR.1943-5452.0000464","volume":"141","author":"D Jung","year":"2015","unstructured":"Jung D, Lansey K (2015) Water distribution system burst detection using a nonlinear Kalman filter. J Water Resour Plan Manag 141(5):04014070","journal-title":"J Water Resour Plan Manag"},{"issue":"3","key":"8497_CR37","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1080\/1573062X.2014.988733","volume":"13","author":"D Loureiro","year":"2016","unstructured":"Loureiro D, Amado C, Martins A, Vitorino D, Mamade A, Coelho ST (2016) Water distribution systems flow monitoring and anomalous event detection: a practical approach. Urban Water J 13(3):242\u2013252","journal-title":"Urban Water J"},{"key":"8497_CR38","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.procs.2016.08.141","volume":"96","author":"F Karray","year":"2016","unstructured":"Karray F, Garcia-Ortiz A, Jmal MW, Obeid AM, Abid M (2016) Earnpipe: a testbed for smart water pipeline monitoring using wireless sensor network. Procedia Comput Sci 96:285\u2013294","journal-title":"Procedia Comput Sci"},{"issue":"3","key":"8497_CR39","doi-asserted-by":"crossref","first-page":"409","DOI":"10.2166\/hydro.2015.113","volume":"18","author":"D Laucelli","year":"2016","unstructured":"Laucelli D, Romano M, Savi\u0107 D, Giustolisi O (2016) Detecting anomalies in water distribution networks using EPR modelling paradigm. J Hydroinf 18(3):409\u2013427","journal-title":"J Hydroinf"},{"issue":"8","key":"8497_CR40","doi-asserted-by":"crossref","first-page":"2719","DOI":"10.1007\/s11269-016-1316-8","volume":"30","author":"SS Leu","year":"2016","unstructured":"Leu SS, Bui QN (2016) Leak prediction model for water distribution networks created using a Bayesian network learning approach. Water Resour Manage 30(8):2719\u20132733","journal-title":"Water Resour Manage"},{"issue":"2","key":"8497_CR41","doi-asserted-by":"crossref","first-page":"146","DOI":"10.3390\/app8020146","volume":"8","author":"Z Jia","year":"2018","unstructured":"Jia Z, Ren L, Li H, Sun W (2018) Pipeline leak localization based on FBG hoop strain sensors combined with BP neural network. Appl Sci 8(2):146","journal-title":"Appl Sci"},{"issue":"1","key":"8497_CR42","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1061\/(ASCE)0733-9496(2010)136:1(116)","volume":"136","author":"ZY Wu","year":"2010","unstructured":"Wu ZY, Sage P, Turtle D (2010) Pressure-dependent leak detection model and its application to a district water system. J Water Resour Plan Manag 136(1):116\u2013128","journal-title":"J Water Resour Plan Manag"},{"issue":"12","key":"8497_CR43","doi-asserted-by":"crossref","first-page":"1765","DOI":"10.3390\/w10121765","volume":"10","author":"P Huang","year":"2018","unstructured":"Huang P, Zhu N, Hou D, Chen J, Xiao Y, Yu J, Zhang H (2018) Real-time burst detection in district metering areas in water distribution system based on patterns of water demand with supervised learning. Water 10(12):1765","journal-title":"Water"},{"key":"8497_CR44","doi-asserted-by":"crossref","unstructured":"G\u00f3mez-Camperos JA, Espinel-Blanco EE, Regino-Ubarnes FJ (2019) Diagnosis of horizontal pipe leaks using neural networks. In: Journal of physics: conference series (Vol. 1388, No. 1, p. 012032). IOP Publishing","DOI":"10.1088\/1742-6596\/1388\/1\/012032"},{"issue":"1","key":"8497_CR45","doi-asserted-by":"crossref","first-page":"54","DOI":"10.3390\/w12010054","volume":"12","author":"C Sun","year":"2019","unstructured":"Sun C, Parellada B, Puig V, Cembrano G (2019) Leak localization in water distribution networks using pressure and data-driven classifier approach. Water 12(1):54","journal-title":"Water"},{"issue":"9","key":"8497_CR46","doi-asserted-by":"crossref","first-page":"3111","DOI":"10.1007\/s11269-019-02296-7","volume":"33","author":"R Rayaroth","year":"2019","unstructured":"Rayaroth R, S G (2019) Random bagging classifier and shuffled frog leaping based optimal sensor placement for leakage detection in WDS. Water Resour Manage 33(9):3111\u20133125","journal-title":"Water Resour Manage"},{"issue":"10","key":"8497_CR47","doi-asserted-by":"crossref","first-page":"648","DOI":"10.3390\/pr7100648","volume":"7","author":"M Zhou","year":"2019","unstructured":"Zhou M, Zhang Q, Liu Y, Sun X, Cai Y, Pan H (2019) An integration method using kernel principal component analysis and cascade support vector data description for pipeline leak detection with multiple operating modes. Processes 7(10):648","journal-title":"Processes"},{"issue":"7","key":"8497_CR48","doi-asserted-by":"crossref","first-page":"1500","DOI":"10.3390\/w11071500","volume":"11","author":"A Soldevila","year":"2019","unstructured":"Soldevila A, Blesa J, Fernandez-Canti RM, Tornil-Sin S, Puig V (2019) Data-driven approach for leak localization in water distribution networks using pressure sensors and spatial interpolation. Water 11(7):1500","journal-title":"Water"},{"key":"8497_CR49","doi-asserted-by":"publisher","DOI":"10.1029\/2019WR025526","author":"X Weirong","year":"2020","unstructured":"Weirong X, Zhou X, Xin K, Boxall J, Yan H, Tao T (2020) Disturbance extraction for burst detection in water distribution networks using pressure measurements. Water Resour Res. https:\/\/doi.org\/10.1029\/2019WR025526","journal-title":"Water Resour Res"},{"key":"8497_CR50","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.watres.2016.05.016","volume":"100","author":"Y Wu","year":"2016","unstructured":"Wu Y, Liu S, Wu X, Liu Y, Guan Y (2016) Burst detection in district metering areas using a data driven clustering algorithm. Water Res 100:28\u201337","journal-title":"Water Res"},{"issue":"2","key":"8497_CR51","doi-asserted-by":"crossref","first-page":"04017084","DOI":"10.1061\/(ASCE)WR.1943-5452.0000870","volume":"144","author":"Y Wu","year":"2018","unstructured":"Wu Y, Liu S, Smith K, Wang X (2018) Using correlation between data from multiple monitoring sensors to detect bursts in water distribution systems. J Water Resour Plan Manag 144(2):04017084","journal-title":"J Water Resour Plan Manag"},{"issue":"10","key":"8497_CR52","doi-asserted-by":"crossref","first-page":"3339","DOI":"10.1007\/s11269-019-02245-4","volume":"33","author":"CV Geelen","year":"2019","unstructured":"Geelen CV, Yntema DR, Molenaar J, Keesman KJ (2019) Monitoring support for water distribution systems based on pressure sensor data. Water Resour Manage 33(10):3339\u20133353","journal-title":"Water Resour Manage"},{"key":"8497_CR53","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/j.watres.2019.03.051","volume":"158","author":"L Xing","year":"2019","unstructured":"Xing L, Sela L (2019) Unsteady pressure patterns discovery from high-frequency sensing in water distribution systems. Water Res 158:291\u2013300","journal-title":"Water Res"},{"key":"8497_CR54","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1007\/978-3-030-21077-9_4","volume-title":"Pattern recognition: 11th Mexican conference, MCPR 2019, Quer\u00e9taro, Mexico, June 26\u201329, 2019, proceedings","author":"M Qui\u00f1ones-Grueiro","year":"2019","unstructured":"Qui\u00f1ones-Grueiro M, Verde C, Llanes-Santiago O (2019) Novel leak location approach in water distribution networks with zone clustering and classification. In: Carrasco-Ochoa JA, Mart\u00ednez-Trinidad JF, Olvera-L\u00f3pez JA, Salas J (eds) Pattern recognition: 11th Mexican conference, MCPR 2019, Quer\u00e9taro, Mexico, June 26\u201329, 2019, proceedings. Springer International Publishing, Cham, pp 37\u201346. https:\/\/doi.org\/10.1007\/978-3-030-21077-9_4"},{"issue":"4","key":"8497_CR55","doi-asserted-by":"crossref","first-page":"1626","DOI":"10.1177\/14759217211040269","volume":"21","author":"X Fan","year":"2021","unstructured":"Fan X, Yu X (2021) An innovative machine learning based framework for water distribution network leakage detection and localization. Struct Health Monit 21(4):1626\u20131644","journal-title":"Struct Health Monit"},{"key":"8497_CR56","doi-asserted-by":"crossref","first-page":"111716","DOI":"10.1016\/j.rse.2020.111716","volume":"241","author":"Q Yuan","year":"2020","unstructured":"Yuan Q, Shen H, Li T, Li Z, Li S, Jiang Y, Zhang L (2020) Deep learning in environmental remote sensing: achievements and challenges. Remote Sens Environ 241:111716","journal-title":"Remote Sens Environ"},{"key":"8497_CR57","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.neucom.2020.04.159","volume":"438","author":"M Qui\u00f1ones-Grueiro","year":"2021","unstructured":"Qui\u00f1ones-Grueiro M, Mili\u00e1n MA, Rivero MS, Neto AJS, Llanes-Santiago O (2021) Robust leak localization in water distribution networks using computational intelligence. Neurocomputing 438:195\u2013208","journal-title":"Neurocomputing"},{"issue":"6","key":"8497_CR58","doi-asserted-by":"crossref","first-page":"04020031","DOI":"10.1061\/(ASCE)WR.1943-5452.0001223","volume":"146","author":"X Wang","year":"2020","unstructured":"Wang X, Guo G, Liu S, Wu Y, Xu X, Smith K (2020) Burst detection in district metering areas using deep learning method. J Water Resour Plan Manag 146(6):04020031","journal-title":"J Water Resour Plan Manag"},{"issue":"5","key":"8497_CR59","doi-asserted-by":"crossref","first-page":"4279","DOI":"10.1109\/TIE.2017.2764861","volume":"65","author":"J Kang","year":"2017","unstructured":"Kang J, Park YJ, Lee J, Wang SH, Eom DS (2017) Novel leakage detection by ensemble CNN-SVM and graph-based localization in water distribution systems. IEEE Trans Industr Electron 65(5):4279\u20134289","journal-title":"IEEE Trans Industr Electron"},{"key":"8497_CR60","doi-asserted-by":"crossref","first-page":"115058","DOI":"10.1016\/j.watres.2019.115058","volume":"166","author":"X Zhou","year":"2019","unstructured":"Zhou X, Tang Z, Xu W, Meng F, Chu X, Xin K, Fu G (2019) Deep learning identifies accurate burst locations in water distribution networks. Water Res 166:115058","journal-title":"Water Res"},{"issue":"5","key":"8497_CR61","doi-asserted-by":"crossref","first-page":"3345","DOI":"10.3934\/mbe.2019167","volume":"16","author":"J Zhang","year":"2019","unstructured":"Zhang J, Lu C, Li X, Kim HJ, Wang J (2019) A full convolutional network based on DenseNet for remote sensing scene classification. Math Biosci Eng 16(5):3345\u20133367","journal-title":"Math Biosci Eng"},{"key":"8497_CR62","doi-asserted-by":"crossref","first-page":"30457","DOI":"10.1109\/ACCESS.2019.2902711","volume":"7","author":"M Zhou","year":"2019","unstructured":"Zhou M, Pan Z, Liu Y, Zhang Q, Cai Y, Pan H (2019) Leak detection and location based on ISLMD and CNN in a pipeline. IEEE Access 7:30457\u201330464","journal-title":"IEEE Access"},{"issue":"2","key":"8497_CR63","doi-asserted-by":"crossref","first-page":"04020001","DOI":"10.1061\/(ASCE)CP.1943-5487.0000881","volume":"34","author":"RA Cody","year":"2020","unstructured":"Cody RA, Tolson BA, Orchard J (2020) Detecting leaks in water distribution pipes using a deep autoencoder and hydroacoustic spectrograms. J Comput Civ Eng 34(2):04020001","journal-title":"J Comput Civ Eng"},{"key":"8497_CR64","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/j.psep.2021.09.033","volume":"155","author":"Z Liao","year":"2021","unstructured":"Liao Z, Yan H, Tang Z, Chu X, Tao T (2021) Deep learning identifies leak in water pipeline system using transient frequency response. Process Saf Environ Prot 155:355\u2013365","journal-title":"Process Saf Environ Prot"},{"issue":"7","key":"8497_CR65","doi-asserted-by":"crossref","first-page":"1031","DOI":"10.1061\/(ASCE)0733-9429(1992)118:7(1031)","volume":"118","author":"RS Pudar","year":"1992","unstructured":"Pudar RS, Liggett JA (1992) Leaks in pipe networks. J Hydraul Eng 118(7):1031\u20131046","journal-title":"J Hydraul Eng"},{"issue":"6","key":"8497_CR66","doi-asserted-by":"crossref","first-page":"715","DOI":"10.2166\/ws.2009.372","volume":"9","author":"R P\u00e9rez","year":"2009","unstructured":"P\u00e9rez R, Puig V, Pascual J, Peralta A, Landeros E, Jordanas L (2009) Pressure sensor distribution for leak detection in Barcelona water distribution network. Water Sci Technol Water Supply 9(6):715\u2013721","journal-title":"Water Sci Technol Water Supply"},{"issue":"10","key":"8497_CR67","doi-asserted-by":"crossref","first-page":"1157","DOI":"10.1016\/j.conengprac.2011.06.004","volume":"19","author":"R P\u00e9rez","year":"2011","unstructured":"P\u00e9rez R, Puig V, Pascual J, Quevedo J, Landeros E, Peralta A (2011) Methodology for leakage isolation using pressure sensitivity analysis in water distribution networks. Control Eng Pract 19(10):1157\u20131167","journal-title":"Control Eng Pract"},{"issue":"4","key":"8497_CR68","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1109\/MCS.2014.2320336","volume":"34","author":"R Perez","year":"2014","unstructured":"Perez R, Sanz G, Puig V, Quevedo J, Escofet MAC, Nejjari F, Sarrate R (2014a) Leak localization in water networks: a model-based methodology using pressure sensors applied to a real network in Barcelona [applications of control]. IEEE Control Syst Mag 34(4):24\u201336","journal-title":"IEEE Control Syst Mag"},{"key":"8497_CR69","doi-asserted-by":"crossref","first-page":"1304","DOI":"10.1016\/j.proeng.2014.02.144","volume":"70","author":"R P\u00e9rez","year":"2014","unstructured":"P\u00e9rez R, Cuguer\u00f3 MA, Cuguer\u00f3 J, Sanz G (2014b) Accuracy assessment of leak localisation method depending on available measurements. Procedia Eng 70:1304\u20131313","journal-title":"Procedia Eng"},{"issue":"3","key":"8497_CR70","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.3390\/w7031129","volume":"7","author":"MV Casillas","year":"2015","unstructured":"Casillas MV, Garza-Casta\u00f1\u00f3n LE, Puig V, Vargas-Martinez A (2015) Leak signature space: an original representation for robust leak location in water distribution networks. Water 7(3):1129\u20131148","journal-title":"Water"},{"issue":"1","key":"8497_CR71","doi-asserted-by":"crossref","first-page":"11","DOI":"10.2166\/ws.2018.048","volume":"19","author":"FJ Salguero","year":"2019","unstructured":"Salguero FJ, Cobacho R, Pardo MA (2019) Unreported leaks location using pressure and flow sensitivity in water distribution networks. Water Supply 19(1):11\u201318","journal-title":"Water Supply"},{"issue":"2","key":"8497_CR72","doi-asserted-by":"crossref","first-page":"04018094","DOI":"10.1061\/(ASCE)WR.1943-5452.0001025","volume":"145","author":"Z Geng","year":"2019","unstructured":"Geng Z, Hu X, Han Y, Zhong Y (2019) A novel leakage-detection method based on sensitivity matrix of pipe flow: case study of water distribution systems. J Water Resour Plan Manag 145(2):04018094","journal-title":"J Water Resour Plan Manag"},{"issue":"24","key":"8497_CR73","doi-asserted-by":"crossref","first-page":"922","DOI":"10.1016\/j.ifacol.2018.09.685","volume":"51","author":"J Jim\u00e9nez-Cabas","year":"2018","unstructured":"Jim\u00e9nez-Cabas J, Romero-Fandi\u00f1o E, Torres L, Sanjuan M, L\u00f3pez-Estrada FR (2018) Localization of leaks in water distribution networks using flow readings. IFAC-PapersOnLine 51(24):922\u2013928","journal-title":"IFAC-PapersOnLine"},{"issue":"7","key":"8497_CR74","doi-asserted-by":"crossref","first-page":"2287","DOI":"10.1007\/s11269-018-1929-1","volume":"32","author":"E Hajibandeh","year":"2018","unstructured":"Hajibandeh E, Nazif S (2018) Pressure zoning approach for leak detection in water distribution systems based on a multi objective ant colony optimization. Water Resour Manage 32(7):2287\u20132300","journal-title":"Water Resour Manage"},{"issue":"03","key":"8497_CR75","doi-asserted-by":"crossref","first-page":"294","DOI":"10.4236\/jwarp.2013.53030","volume":"05","author":"A Nasirian","year":"2013","unstructured":"Nasirian A, Maghrebi MF, Yazdani S (2013) Leakage detection in water distribution network based on a new heuristic genetic algorithm model. J Water Resour Prot 05(03):294\u2013303","journal-title":"J Water Resour Prot"},{"issue":"2","key":"8497_CR76","doi-asserted-by":"crossref","first-page":"04015057","DOI":"10.1061\/(ASCE)WR.1943-5452.0000592","volume":"142","author":"G Sanz","year":"2016","unstructured":"Sanz G, P\u00e9rez R, Kapelan Z, Savic D (2016) Leak detection and localization through demand components calibration. J Water Resour Plan Manag 142(2):04015057","journal-title":"J Water Resour Plan Manag"},{"issue":"2","key":"8497_CR77","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/j.aei.2013.01.001","volume":"27","author":"JA Goulet","year":"2013","unstructured":"Goulet JA, Coutu S, Smith IF (2013) Model falsification diagnosis and sensor placement for leak detection in pressurized pipe networks. Adv Eng Inform 27(2):261\u2013269","journal-title":"Adv Eng Inform"},{"issue":"3","key":"8497_CR78","doi-asserted-by":"crossref","first-page":"714","DOI":"10.1016\/j.aei.2015.07.003","volume":"29","author":"G Moser","year":"2015","unstructured":"Moser G, Paal SG, Smith IF (2015) Performance comparison of reduced models for leak detection in water distribution networks. Adv Eng Inform 29(3):714\u2013726","journal-title":"Adv Eng Inform"},{"issue":"4","key":"8497_CR79","doi-asserted-by":"crossref","first-page":"672","DOI":"10.1016\/j.aei.2016.09.003","volume":"30","author":"G Moser","year":"2016","unstructured":"Moser G, Paal SG, Jlelaty D, Smith IF (2016) An electrical network for evaluating monitoring strategies intended for hydraulic pressurized networks. Adv Eng Inform 30(4):672\u2013686","journal-title":"Adv Eng Inform"},{"key":"8497_CR80","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.ress.2018.12.014","volume":"185","author":"HA Jensen","year":"2019","unstructured":"Jensen HA, Jerez DJ (2019) A Bayesian model updating approach for detection-related problems in water distribution networks. Reliab Eng Syst Saf 185:100\u2013112","journal-title":"Reliab Eng Syst Saf"},{"issue":"2","key":"8497_CR81","doi-asserted-by":"crossref","first-page":"04017077","DOI":"10.1061\/(ASCE)CP.1943-5487.0000729","volume":"32","author":"G Moser","year":"2018","unstructured":"Moser G, Paal SG, Smith IF (2018) Leak detection of water supply networks using error-domain model falsification. J Comput Civ Eng 32(2):04017077","journal-title":"J Comput Civ Eng"},{"issue":"14","key":"8497_CR82","doi-asserted-by":"crossref","first-page":"3070","DOI":"10.3390\/s19143070","volume":"19","author":"Y Shao","year":"2019","unstructured":"Shao Y, Li X, Zhang T, Chu S, Liu X (2019) Time-series-based leakage detection using multiple pressure sensors in water distribution systems. Sensors 19(14):3070","journal-title":"Sensors"},{"key":"8497_CR83","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1016\/j.ins.2016.01.033","volume":"340","author":"X Deng","year":"2016","unstructured":"Deng X, Liu Q, Deng Y, Mahadevan S (2016) An improved method to construct basic probability assignment based on the confusion matrix for classification problem. Inf Sci 340:250\u2013261","journal-title":"Inf Sci"},{"issue":"4","key":"8497_CR84","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1061\/(ASCE)WR.1943-5452.0000339","volume":"140","author":"M Romano","year":"2014","unstructured":"Romano M, Kapelan Z, Savi\u0107 DA (2014) Automated detection of pipe bursts and other events in water distribution systems. J Water Resour Plan Manag 140(4):457\u2013467","journal-title":"J Water Resour Plan Manag"},{"issue":"5","key":"8497_CR85","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1061\/(ASCE)WR.1943-5452.0000347","volume":"140","author":"M Romano","year":"2014","unstructured":"Romano M, Kapelan Z, Savi\u0107 DA (2014) Evolutionary algorithm and expectation maximization strategies for improved detection of pipe bursts and other events in water distribution systems. J Water Resour Plan Manag 140(5):572\u2013584","journal-title":"J Water Resour Plan Manag"},{"issue":"1","key":"8497_CR86","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11265-012-0690-6","volume":"72","author":"S Srirangarajan","year":"2013","unstructured":"Srirangarajan S, Allen M, Preis A, Iqbal M, Lim HB, Whittle AJ (2013) Wavelet-based burst event detection and localization in water distribution systems. J Sign Process Syst 72(1):1\u201316","journal-title":"J Sign Process Syst"},{"issue":"10","key":"8497_CR87","doi-asserted-by":"crossref","first-page":"04014027","DOI":"10.1061\/(ASCE)WR.1943-5452.0000405","volume":"140","author":"T Tao","year":"2014","unstructured":"Tao T, Huang H, Li F, Xin K (2014) Burst detection using an artificial immune network in water-distribution systems. J Water Resour Plan Manag 140(10):04014027","journal-title":"J Water Resour Plan Manag"},{"issue":"12","key":"8497_CR88","doi-asserted-by":"crossref","first-page":"4134","DOI":"10.1109\/JSEN.2014.2358842","volume":"14","author":"TTT Zan","year":"2014","unstructured":"Zan TTT, Lim HB, Wong KJ, Whittle AJ, Lee BS (2014) Event detection and localization in urban water distribution network. IEEE Sens J 14(12):4134\u20134142","journal-title":"IEEE Sens J"},{"issue":"11","key":"8497_CR89","doi-asserted-by":"crossref","first-page":"04016042","DOI":"10.1061\/(ASCE)WR.1943-5452.0000661","volume":"142","author":"Q Zhang","year":"2016","unstructured":"Zhang Q, Wu ZY, Zhao M, Qi J, Huang Y, Zhao H (2016) Leakage zone identification in large-scale water distribution systems using multiclass support vector machines. J Water Resour Plan Manag 142(11):04016042","journal-title":"J Water Resour Plan Manag"},{"key":"8497_CR90","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.conengprac.2016.07.006","volume":"55","author":"A Soldevila","year":"2016","unstructured":"Soldevila A, Blesa J, Tornil-Sin S, Duviella E, Fernandez-Canti RM, Puig V (2016) Leak localization in water distribution networks using a mixed model-based\/data-driven approach. Control Eng Pract 55:162\u2013173","journal-title":"Control Eng Pract"},{"key":"8497_CR91","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jprocont.2017.03.015","volume":"55","author":"A Soldevila","year":"2017","unstructured":"Soldevila A, Fernandez-Canti RM, Blesa J, Tornil-Sin S, Puig V (2017) Leak localization in water distribution networks using Bayesian classifiers. J Process Control 55:1\u20139","journal-title":"J Process Control"},{"issue":"6","key":"8497_CR92","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.2166\/ws.2014.063","volume":"14","author":"M Bakker","year":"2014","unstructured":"Bakker M, Trietsch EA, Vreeburg JHG, Rietveld LC (2014b) Analysis of historic bursts and burst detection in water supply areas of different size. Water Sci Technol Water Supply 14(6):1035\u20131044","journal-title":"Water Sci Technol Water Supply"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08497-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-023-08497-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08497-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,11]],"date-time":"2023-05-11T17:27:16Z","timestamp":1683826036000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-023-08497-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,6]]},"references-count":92,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2023,6]]}},"alternative-id":["8497"],"URL":"https:\/\/doi.org\/10.1007\/s00521-023-08497-x","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,6]]},"assertion":[{"value":"20 September 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 March 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 April 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":"There is no conflict of interest associated with this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}