{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T14:19:32Z","timestamp":1776176372037,"version":"3.50.1"},"reference-count":58,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,5,15]],"date-time":"2020-05-15T00:00:00Z","timestamp":1589500800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,5,15]],"date-time":"2020-05-15T00:00:00Z","timestamp":1589500800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61673354"],"award-info":[{"award-number":["61673354"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1911205"],"award-info":[{"award-number":["U1911205"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2021,1]]},"DOI":"10.1007\/s00521-020-05000-8","type":"journal-article","created":{"date-parts":[[2020,5,15]],"date-time":"2020-05-15T13:18:57Z","timestamp":1589548737000},"page":"209-222","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Pollution source intelligent location algorithm in water quality sensor networks"],"prefix":"10.1007","volume":"33","author":[{"given":"Xuesong","family":"Yan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingyu","family":"Gong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qinghua","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,5,15]]},"reference":[{"key":"5000_CR1","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1007\/s00521-012-0940-3","volume":"22","author":"A Najah","year":"2013","unstructured":"Najah A, El-Shafie A, Karim OA et al (2013) Application of artificial neural networks for water quality prediction. Neural Comput Appl 22:187\u2013201","journal-title":"Neural Comput Appl"},{"key":"5000_CR2","doi-asserted-by":"crossref","first-page":"893","DOI":"10.1007\/s00521-016-2404-7","volume":"28","author":"M Hameed","year":"2017","unstructured":"Hameed M, Sharqi SS, Yaseen ZM et al (2017) Application of artificial intelligence (AI) techniques in water quality index prediction: a case study in tropical region, Malaysia. Neural Comput Appl 28:893\u2013905","journal-title":"Neural Comput Appl"},{"key":"5000_CR3","doi-asserted-by":"crossref","first-page":"2905","DOI":"10.1007\/s00521-017-2872-4","volume":"28","author":"F Kayaalp","year":"2017","unstructured":"Kayaalp F, Zengin A, Kara R et al (2017) Leakage detection and localization on water transportation pipelines: a multi-label classification approach. Neural Comput Appl 28:2905\u20132914","journal-title":"Neural Comput Appl"},{"key":"5000_CR4","doi-asserted-by":"crossref","first-page":"3763","DOI":"10.1007\/s00521-018-3768-7","volume":"32","author":"O Mohammadrezapour","year":"2020","unstructured":"Mohammadrezapour O, Kisi O, Pourahmad F (2020) Fuzzy c-means and K-means clustering with genetic algorithm for identification of homogeneous regions of groundwater quality. Neural Comput Appl 32:3763\u20133775","journal-title":"Neural Comput Appl"},{"issue":"5","key":"5000_CR5","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1061\/(ASCE)0733-9372(2002)128:5(441)","volume":"128","author":"F Shang","year":"2002","unstructured":"Shang F, Uber JG, Polycarpou MM (2002) Particle backtracking algorithm for water distribution system analysis. J Environ Eng 128(5):441\u2013450","journal-title":"J Environ Eng"},{"issue":"2","key":"5000_CR6","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1061\/(ASCE)0733-9496(2005)131:2(125)","volume":"131","author":"CD Laird","year":"2005","unstructured":"Laird CD, Biegler LT, van Bloemen Waanders BG, Bartlett RA (2005) Contamination source determination for water networks. J Water Resour Plan Manag 131(2):125\u2013134","journal-title":"J Water Resour Plan Manag"},{"issue":"4","key":"5000_CR7","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1061\/(ASCE)WR.1943-5452.0000050","volume":"136","author":"AE De Sanctis","year":"2009","unstructured":"De Sanctis AE, Shang F, Uber JG (2009) Real-time identification of possible contamination sources using network backtracking methods. J Water Resour Plan Manag 136(4):444\u2013453","journal-title":"J Water Resour Plan Manag"},{"issue":"13","key":"5000_CR8","doi-asserted-by":"crossref","first-page":"4623","DOI":"10.1007\/s11269-013-0431-z","volume":"27","author":"DM Costa","year":"2013","unstructured":"Costa DM, Melo LF, Martins FG (2013) Localization of contamination sources in drinking water distribution systems: a method based on successive positive readings of sensors. Water Resour Manag 27(13):4623\u20134635","journal-title":"Water Resour Manag"},{"issue":"6","key":"5000_CR9","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1061\/(ASCE)0733-9496(2009)135:6(466)","volume":"135","author":"JJ Huang","year":"2009","unstructured":"Huang JJ, McBean EA (2009) Data mining to identify contaminant event locations in water distribution systems. J Water Resour Plan Manag 135(6):466\u2013474","journal-title":"J Water Resour Plan Manag"},{"issue":"4","key":"5000_CR10","doi-asserted-by":"crossref","first-page":"426","DOI":"10.1061\/(ASCE)WR.1943-5452.0000288","volume":"139","author":"L Perelman","year":"2012","unstructured":"Perelman L, Ostfeld A (2012) Bayesian networks for source intrusion detection. J Water Resour Plan Manag 139(4):426\u2013432","journal-title":"J Water Resour Plan Manag"},{"issue":"1","key":"5000_CR11","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1061\/(ASCE)WR.1943-5452.0000323","volume":"140","author":"H Wang","year":"2012","unstructured":"Wang H, Harrison KW (2012) Improving efficiency of the Bayesian approach to water distribution contaminant source characterization with support vector regression. J Water Resour Plan Manag 140(1):3\u201311","journal-title":"J Water Resour Plan Manag"},{"issue":"4","key":"5000_CR12","doi-asserted-by":"crossref","first-page":"867","DOI":"10.1007\/s00477-012-0622-9","volume":"27","author":"H Wang","year":"2013","unstructured":"Wang H, Jin X (2013) Characterization of groundwater contaminant source using Bayesian method. Stoch Environ Res Risk Assess 27(4):867\u2013876","journal-title":"Stoch Environ Res Risk Assess"},{"issue":"3","key":"5000_CR13","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1007\/s00521-016-2572-5","volume":"30","author":"Y-N Guo","year":"2018","unstructured":"Guo Y-N, Pei Z, Cheng J, Wang C, Gong D (2018) Interval multi-objective quantum-inspired cultural algorithms. Neural Comput Appl 30(3):709\u2013722","journal-title":"Neural Comput Appl"},{"issue":"9","key":"5000_CR14","doi-asserted-by":"crossref","first-page":"4577","DOI":"10.1007\/s00521-018-3457-6","volume":"31","author":"X Yan","year":"2019","unstructured":"Yan X, Zhu Z, Hu C, Gong W, Wu Q (2019) Spark-based intelligent parameter inversion method for prestack seismic data. Neural Comput Appl 31(9):4577\u20134593","journal-title":"Neural Comput Appl"},{"key":"5000_CR15","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2018.2828018","author":"W Gong","year":"2018","unstructured":"Gong W, Wang Y, Cai Z, Wang L (2018) Finding multiple roots of nonlinear equation systems via a repulsion-based adaptive differential evolution. IEEE Trans Syst Man Cybern Syst. https:\/\/doi.org\/10.1109\/TSMC.2018.2828018","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"issue":"7","key":"5000_CR16","doi-asserted-by":"crossref","first-page":"6335","DOI":"10.1016\/j.eswa.2011.12.017","volume":"39","author":"B Wu","year":"2012","unstructured":"Wu B, Qian C, Ni W, Fan S (2012) The improvement of glowworm swarm optimization for continuous optimization problems. Expert Syst Appl 39(7):6335\u20136342","journal-title":"Expert Syst Appl"},{"key":"5000_CR17","doi-asserted-by":"crossref","first-page":"773","DOI":"10.1016\/j.jclepro.2018.06.137","volume":"196","author":"C Lu","year":"2018","unstructured":"Lu C, Gao L, Li X, Zheng J, Gong W (2018) A multi-objective approach to welding shop scheduling for makespan, noise pollution and energy consumption. J Clean Prod 196:773\u2013787","journal-title":"J Clean Prod"},{"issue":"9","key":"5000_CR18","first-page":"1","volume":"31","author":"Q Wu","year":"2019","unstructured":"Wu Q, Zhu Z, Yan X, Gong W (2019) An improved particle swarm optimization algorithm for AVO elastic parameter inversion problem. Concurr Comput Pract Exp 31(9):1\u201316","journal-title":"Concurr Comput Pract Exp"},{"issue":"6","key":"5000_CR19","doi-asserted-by":"crossref","first-page":"1609","DOI":"10.1007\/s00521-019-04212-x","volume":"32","author":"P Yu","year":"2020","unstructured":"Yu P, Yan X (2020) Stock price prediction based on deep neural network. Neural Comput Appl 32(6):1609\u20131628","journal-title":"Neural Comput Appl"},{"key":"5000_CR20","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/j.solener.2013.05.007","volume":"94","author":"W Gong","year":"2013","unstructured":"Gong W, Cai Z (2013) Parameter extraction of solar cell models using repaired adaptive differential evolution. Sol Energy 94:209\u2013220","journal-title":"Sol Energy"},{"issue":"23","key":"5000_CR21","doi-asserted-by":"crossref","first-page":"7833","DOI":"10.1007\/s00500-018-3499-9","volume":"22","author":"F Wang","year":"2018","unstructured":"Wang F, Zhang H, Li Y, Zhao Y, Rao Q (2018) External archive matching strategy for MOEA\/D. Soft Comput 22(23):7833\u20137846","journal-title":"Soft Comput"},{"issue":"10","key":"5000_CR22","doi-asserted-by":"crossref","first-page":"2382","DOI":"10.1109\/TKDE.2013.2297923","volume":"26","author":"J Wu","year":"2014","unstructured":"Wu J, Zhu X, Zhang C, Yu PS (2014) Bag constrained structure pattern mining for multi-graph classification. IEEE Trans Knowl Data Eng 26(10):2382\u20132396","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"5000_CR23","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.ins.2017.09.053","volume":"423","author":"G Wu","year":"2018","unstructured":"Wu G, Shen X, Li H, Chen H, Lin A, Suganthan PN (2018) Ensemble of differential evolution variants. Inf Sci 423:172\u2013186","journal-title":"Inf Sci"},{"issue":"6","key":"5000_CR24","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.1109\/TKDE.2017.2788430","volume":"30","author":"J Wu","year":"2018","unstructured":"Wu J, Pan S, Zhu X, Zhang C, Wu X (2018) Multi-instance learning with discriminative bag mapping. IEEE Trans Knowl Data Eng 30(6):1065\u20131080","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"5000_CR25","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1109\/TEVC.2016.2611642","volume":"22","author":"R Wang","year":"2018","unstructured":"Wang R, Ishibuchi H, Zhou Z, Liao T, Zhang T (2018) Localized weighted sum method for many-objective optimization. IEEE Trans Evol Comput 22:3\u201318","journal-title":"IEEE Trans Evol Comput"},{"key":"5000_CR26","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.eswa.2018.04.012","volume":"107","author":"C Lu","year":"2018","unstructured":"Lu C, Gao L, Yi J (2018) Grey wolf optimizer with cellular topological structure. Expert Syst Appl 107:89\u2013114","journal-title":"Expert Syst Appl"},{"issue":"1","key":"5000_CR27","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1109\/TEVC.2017.2672689","volume":"22","author":"P Yang","year":"2018","unstructured":"Yang P, Tang K, Yao X (2018) Turning high-dimensional optimization into computationally expensive optimization. IEEE Trans Evol Comput 22(1):143\u2013156","journal-title":"IEEE Trans Evol Comput"},{"key":"5000_CR28","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.ins.2018.01.027","volume":"436\u2013437","author":"F Wang","year":"2018","unstructured":"Wang F, Zhang H, Li K, Lin Z, Yang J, Shen X-L (2018) A hybrid particle swarm optimization algorithm using adaptive learning strategy. Inf Sci 436\u2013437:162\u2013177","journal-title":"Inf Sci"},{"key":"5000_CR29","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.swevo.2019.03.015","volume":"48","author":"Y-N Guo","year":"2019","unstructured":"Guo Y-N, Yang H, Chen M, Cheng J, Gong D (2019) Ensemble prediction-based dynamic robust multi-objective optimization methods. Swarm Evol Comput 48:156\u2013171","journal-title":"Swarm Evol Comput"},{"key":"5000_CR30","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.ins.2019.12.083","volume":"517","author":"X Yan","year":"2020","unstructured":"Yan X, Li P, Tang K, Gao L, Wang L (2020) Clonal selection based intelligent parameter inversion algorithm for prestack seismic data. Inf Sci 517:86\u201399","journal-title":"Inf Sci"},{"key":"5000_CR31","doi-asserted-by":"crossref","first-page":"488","DOI":"10.1016\/j.ins.2018.06.055","volume":"509","author":"C Hu","year":"2020","unstructured":"Hu C, Dai L, Yan X, Gong W, Liu X, Wang L (2020) Modified NSGA-III for sensor placement in water distribution system. Inf Sci 509:488\u2013500","journal-title":"Inf Sci"},{"issue":"3","key":"5000_CR32","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1109\/TCYB.2014.2327246","volume":"45","author":"J Wu","year":"2015","unstructured":"Wu J, Pan S, Zhu X, Cai Z (2015) Boosting for multi-graph classification. IEEE Trans Cybern 45(3):430\u2013443","journal-title":"IEEE Trans Cybern"},{"issue":"3","key":"5000_CR33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/JSAC.2016.2525458","volume":"34","author":"K Tang","year":"2016","unstructured":"Tang K, Yang P, Yao X (2016) Negatively correlated search. IEEE J Sel Areas Commun 34(3):1\u20139","journal-title":"IEEE J Sel Areas Commun"},{"key":"5000_CR34","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.ins.2019.04.017","volume":"492","author":"J Shi","year":"2019","unstructured":"Shi J, Lei Y, Wu J et al (2019) Uncertain active contour model based on rough and fuzzy sets for auroral oval segmentation. Inf Sci 492:72\u2013103","journal-title":"Inf Sci"},{"key":"5000_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2019.101436","author":"Y Lei","year":"2019","unstructured":"Lei Y, Zhou Y, Shi J (2019) Overlapping communities detection of social network based on hybrid c-means clustering algorithm. Sustain Cities Soc. https:\/\/doi.org\/10.1016\/j.scs.2019.101436","journal-title":"Sustain Cities Soc"},{"key":"5000_CR36","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1016\/j.solener.2019.08.022","volume":"190","author":"S Li","year":"2019","unstructured":"Li S, Gong W, Yan X, Hu C, Bai D, Wang L (2019) Parameter estimation of photovoltaic models with memetic adaptive differential evolution. Sol Energy 190:465\u2013474","journal-title":"Sol Energy"},{"key":"5000_CR37","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.swevo.2019.06.009","volume":"49","author":"F Wang","year":"2019","unstructured":"Wang F, Li Y, Zhang H, Hu T, Shen X-L (2019) An adaptive weight vector guided evolutionary algorithm for preference-based multi-objective optimization. Swarm Evol Comput 49:220\u2013233","journal-title":"Swarm Evol Comput"},{"issue":"3","key":"5000_CR38","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1080\/10286600500308144","volume":"22","author":"A Ostfeld","year":"2005","unstructured":"Ostfeld A, Salomons E (2005) Optimal early warning monitoring system layout for water networks security: inclusion of sensors sensitivities and response delays. Civ Eng Environ Syst 22(3):151\u2013169","journal-title":"Civ Eng Environ Syst"},{"issue":"4","key":"5000_CR39","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1061\/(ASCE)0733-9496(2006)132:4(252)","volume":"132","author":"J Guan","year":"2006","unstructured":"Guan J, Aral MM, Maslia ML, Grayman WM (2006) Identification of contaminant sources in water distribution systems using simulation\u2013optimization method: case study. J Water Resour Plan Manag 132(4):252\u2013262","journal-title":"J Water Resour Plan Manag"},{"issue":"8","key":"5000_CR40","doi-asserted-by":"crossref","first-page":"941","DOI":"10.1080\/03052150701540670","volume":"39","author":"A Preis","year":"2007","unstructured":"Preis A, Ostfeld A (2007) A contamination source identification model for water distribution system security. Eng Optim 39(8):941\u2013947","journal-title":"Eng Optim"},{"issue":"1","key":"5000_CR41","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1080\/10286600701695471","volume":"25","author":"A Preis","year":"2008","unstructured":"Preis A, Ostfeld A (2008) Genetic algorithm for contaminant source characterization using imperfect sensors. Civ Eng Environ Syst 25(1):29\u201339","journal-title":"Civ Eng Environ Syst"},{"issue":"5","key":"5000_CR42","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1061\/(ASCE)0733-9496(2009)135:5(334)","volume":"135","author":"EM Zechman","year":"2009","unstructured":"Zechman EM, Ranjithan SR (2009) Evolutionary computation-based methods for characterizing contaminant sources in a water distribution system. J Water Resour Plan Manag 135(5):334\u2013343","journal-title":"J Water Resour Plan Manag"},{"issue":"3","key":"5000_CR43","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1080\/15275920903140486","volume":"10","author":"P Vankayala","year":"2009","unstructured":"Vankayala P, Sankarasubramanian A, Ranjithan SR et al (2009) Contaminant source identification in water distribution networks under conditions of demand uncertainty. Environ Forensics 10(3):253\u2013263","journal-title":"Environ Forensics"},{"key":"5000_CR44","first-page":"484","volume":"3","author":"M Lv","year":"2010","unstructured":"Lv M, Wang M, Liu J, Dong S (2010) Notice of retraction investigation on backward tracking of contamination sources in water supply systems-case study. Int Conf Environ Sci Inf Appl Technol 3:484\u2013487","journal-title":"Int Conf Environ Sci Inf Appl Technol"},{"key":"5000_CR45","first-page":"24","volume":"2011","author":"K Drake","year":"2011","unstructured":"Drake K, Zechman E (2011) Using niched co-evolution strategies to address non-uniqueness in characterizing sources of contamination in a water distribution system. World Environ Water Resour Congr 2011:24\u2013329","journal-title":"World Environ Water Resour Congr"},{"issue":"2","key":"5000_CR46","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1061\/(ASCE)WR.1943-5452.0000104","volume":"137","author":"L Liu","year":"2010","unstructured":"Liu L, Ranjithan SR, Mahinthakumar G (2010) Contamination source identification in water distribution systems using an adaptive dynamic optimization procedure. J Water Resour Plan Manag 137(2):183\u2013192","journal-title":"J Water Resour Plan Manag"},{"issue":"C","key":"5000_CR47","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.adhoc.2015.07.011","volume":"35","author":"C Hu","year":"2015","unstructured":"Hu C, Zhao J, Yan X, Zeng D, Guo S (2015) A mapreduce based parallel niche genetic algorithm for contaminant source identification in water distribution network. Ad Hoc Netw 35(C):116\u2013126","journal-title":"Ad Hoc Netw"},{"issue":"2","key":"5000_CR48","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1007\/s10586-017-0787-6","volume":"20","author":"X Yan","year":"2017","unstructured":"Yan X, Sun J, Hu C (2017) Research on contaminant sources identification of uncertainty water demand using genetic algorithm. Clust Comput 20(2):1007\u20131016","journal-title":"Clust Comput"},{"issue":"24","key":"5000_CR49","first-page":"1","volume":"29","author":"X Yan","year":"2017","unstructured":"Yan X, Gong W, Wu Q (2017) Contaminant source identification of water distribution networks using cultural algorithm. Concurr Comput Pract Exp 29(24):1\u201311","journal-title":"Concurr Comput Pract Exp"},{"key":"5000_CR50","doi-asserted-by":"crossref","first-page":"308","DOI":"10.5004\/dwt.2018.22330","volume":"110","author":"X Yan","year":"2018","unstructured":"Yan X, Yang K, Hu C (2018) Pollution source positioning in a water supply network based on expensive optimization. Desalin Water Treat 110:308\u2013318","journal-title":"Desalin Water Treat"},{"key":"5000_CR51","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.swevo.2017.05.010","volume":"47","author":"X Yan","year":"2019","unstructured":"Yan X, Zhao J et al (2019) Multimodal optimization problem in contamination source determination of water supply networks. Swarm Evol Comput 47:66\u201371","journal-title":"Swarm Evol Comput"},{"issue":"18","key":"5000_CR52","doi-asserted-by":"crossref","first-page":"17901","DOI":"10.1007\/s11356-017-0516-y","volume":"26","author":"X Yan","year":"2019","unstructured":"Yan X, Zhu Z, Li T (2019) Pollution source localization in an urban water supply network based on dynamic water demand. Environ Sci Pollut Res 26(18):17901\u201317910","journal-title":"Environ Sci Pollut Res"},{"key":"5000_CR53","doi-asserted-by":"crossref","first-page":"123","DOI":"10.5004\/dwt.2019.24204","volume":"168","author":"Jinyu Gong","year":"2019","unstructured":"Gong Jinyu, Yan Xuesong, Chengyu Hu, Qinghua Wu (2019) Collaborative based pollution sources identification algorithm in water supply sensor networks. Desalin Water Treat 168:123\u2013135","journal-title":"Desalin Water Treat"},{"key":"5000_CR54","doi-asserted-by":"crossref","first-page":"5941","DOI":"10.1007\/s10586-018-1725-y","volume":"22","author":"X Yan","year":"2019","unstructured":"Yan X, Li T, Hu C (2019) Real-time localization of pollution source for urban water supply network in emergencies. Clust Comput 22:5941\u20135954","journal-title":"Clust Comput"},{"key":"5000_CR55","first-page":"115","volume-title":"Epanet 2 users manual","author":"LA Rossman","year":"2000","unstructured":"Rossman LA (2000) Epanet 2 users manual, vol 19(1). Laboratory Office of Research & Development United States Environmental Protection Agency, Cincinnati, pp 115\u2013118"},{"key":"5000_CR56","first-page":"169","volume-title":"Handbook of poisson distribution","author":"FA Haight","year":"1967","unstructured":"Haight FA (1967) Handbook of poisson distribution. Wiley, New York, pp 169\u2013179"},{"issue":"4","key":"5000_CR57","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1080\/00401706.1973.10489112","volume":"15","author":"PC Consul","year":"1973","unstructured":"Consul PC, Jain GC (1973) A generalization of the Poisson distribution. Technometrics 15(4):791\u2013799","journal-title":"Technometrics"},{"key":"5000_CR58","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1002\/0471715816.ch4","volume-title":"Poisson distribution. Univariate discrete distributions","author":"NL Johnson","year":"2005","unstructured":"Johnson NL, Kemp AW, Kotz S (2005) Poisson distribution. Univariate discrete distributions, 3rd edn. Wiley, New York, pp 156\u2013207","edition":"3"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-05000-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-020-05000-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-05000-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,14]],"date-time":"2021-05-14T23:30:32Z","timestamp":1621035032000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-020-05000-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,15]]},"references-count":58,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["5000"],"URL":"https:\/\/doi.org\/10.1007\/s00521-020-05000-8","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,15]]},"assertion":[{"value":"7 February 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 May 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 May 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare there is no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}