{"id":"https://openalex.org/W4412804827","doi":"https://doi.org/10.1061/jccee5.cpeng-6119","title":"Explainable Machine-Learning Leak Identification Framework for Water Distribution Networks","display_name":"Explainable Machine-Learning Leak Identification Framework for Water Distribution Networks","publication_year":2025,"publication_date":"2025-07-31","ids":{"openalex":"https://openalex.org/W4412804827","doi":"https://doi.org/10.1061/jccee5.cpeng-6119"},"language":"en","primary_location":{"id":"doi:10.1061/jccee5.cpeng-6119","is_oa":false,"landing_page_url":"https://doi.org/10.1061/jccee5.cpeng-6119","pdf_url":null,"source":{"id":"https://openalex.org/S176637136","display_name":"Journal of Computing in Civil Engineering","issn_l":"0887-3801","issn":["0887-3801","1943-5487"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315747","host_organization_name":"American Society of Civil Engineers","host_organization_lineage":["https://openalex.org/P4310315747"],"host_organization_lineage_names":["American Society of Civil Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing in Civil Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102895030","display_name":"Rongsheng Liu","orcid":"https://orcid.org/0000-0002-8390-9599"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Rongsheng Liu","raw_affiliation_strings":["Hong Kong Polytechnic Univ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong Polytechnic Univ","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091382230","display_name":"Tarek Zayed","orcid":"https://orcid.org/0000-0003-3249-7712"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Tarek Zayed","raw_affiliation_strings":["Hong Kong Polytechnic Univ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong Polytechnic Univ","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035639517","display_name":"Rui Xiao","orcid":"https://orcid.org/0000-0001-9295-9793"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Rui Xiao","raw_affiliation_strings":["Hong Kong Polytechnic Univ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong Polytechnic Univ","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I14243506"],"apc_list":null,"apc_paid":null,"fwci":0.567,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.66038351,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"39","issue":"6","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11220","display_name":"Water Systems and Optimization","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11220","display_name":"Water Systems and Optimization","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13429","display_name":"Electricity Theft Detection Techniques","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/leak-detection","display_name":"Leak detection","score":0.7293447256088257},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6605067253112793},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5382738709449768},{"id":"https://openalex.org/keywords/leak","display_name":"Leak","score":0.47336432337760925},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.36573582887649536},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.35481393337249756},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.347440242767334},{"id":"https://openalex.org/keywords/environmental-engineering","display_name":"Environmental engineering","score":0.14982500672340393}],"concepts":[{"id":"https://openalex.org/C2987355568","wikidata":"https://www.wikidata.org/wiki/Q4420957","display_name":"Leak detection","level":3,"score":0.7293447256088257},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6605067253112793},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5382738709449768},{"id":"https://openalex.org/C2780378346","wikidata":"https://www.wikidata.org/wiki/Q1349983","display_name":"Leak","level":2,"score":0.47336432337760925},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.36573582887649536},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.35481393337249756},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.347440242767334},{"id":"https://openalex.org/C87717796","wikidata":"https://www.wikidata.org/wiki/Q146326","display_name":"Environmental engineering","level":1,"score":0.14982500672340393},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1061/jccee5.cpeng-6119","is_oa":false,"landing_page_url":"https://doi.org/10.1061/jccee5.cpeng-6119","pdf_url":null,"source":{"id":"https://openalex.org/S176637136","display_name":"Journal of Computing in Civil Engineering","issn_l":"0887-3801","issn":["0887-3801","1943-5487"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315747","host_organization_name":"American Society of Civil Engineers","host_organization_lineage":["https://openalex.org/P4310315747"],"host_organization_lineage_names":["American Society of Civil Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing in Civil Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8100000023841858,"display_name":"Clean water and sanitation","id":"https://metadata.un.org/sdg/6"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W598308944","https://openalex.org/W1523493493","https://openalex.org/W1686810756","https://openalex.org/W2000982976","https://openalex.org/W2031833169","https://openalex.org/W2074299896","https://openalex.org/W2114446345","https://openalex.org/W2145487065","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2257307118","https://openalex.org/W2283544056","https://openalex.org/W2295107390","https://openalex.org/W2509453848","https://openalex.org/W2561115530","https://openalex.org/W2562090963","https://openalex.org/W2604839236","https://openalex.org/W2745606177","https://openalex.org/W2764024122","https://openalex.org/W2771213212","https://openalex.org/W2811111357","https://openalex.org/W2884106773","https://openalex.org/W2916091221","https://openalex.org/W2919115771","https://openalex.org/W2962772482","https://openalex.org/W2962858109","https://openalex.org/W2980113592","https://openalex.org/W2999052398","https://openalex.org/W3006342871","https://openalex.org/W3012539788","https://openalex.org/W3021139004","https://openalex.org/W3097789521","https://openalex.org/W3109136062","https://openalex.org/W3131351795","https://openalex.org/W3153235687","https://openalex.org/W3165575792","https://openalex.org/W3185942495","https://openalex.org/W3202688760","https://openalex.org/W3204690116","https://openalex.org/W3206489419","https://openalex.org/W3213452644","https://openalex.org/W3217424478","https://openalex.org/W4200440966","https://openalex.org/W4206569030","https://openalex.org/W4281718600","https://openalex.org/W4283804353","https://openalex.org/W4289745752","https://openalex.org/W4315866203","https://openalex.org/W4323306150","https://openalex.org/W4323654767","https://openalex.org/W4362723280","https://openalex.org/W4377107874","https://openalex.org/W4379644456","https://openalex.org/W4381936631","https://openalex.org/W4382293034","https://openalex.org/W4382399592","https://openalex.org/W4386474352","https://openalex.org/W4389503541","https://openalex.org/W4393149817","https://openalex.org/W4394589447","https://openalex.org/W4400532948","https://openalex.org/W4402576233","https://openalex.org/W4405950959"],"related_works":["https://openalex.org/W2357422790","https://openalex.org/W1968766800","https://openalex.org/W1553563528","https://openalex.org/W2089419128","https://openalex.org/W2271340062","https://openalex.org/W2356864307","https://openalex.org/W4389695218","https://openalex.org/W2371267147","https://openalex.org/W2391748782","https://openalex.org/W1997045795"],"abstract_inverted_index":{"Leak":[0],"identification":[1,76,131,164,250,270],"in":[2,43,97],"urban":[3],"water":[4,74],"distribution":[5],"networks":[6,18],"(WDNs)":[7],"is":[8],"a":[9,41,47,190],"critical":[10],"task":[11],"with":[12,30,248],"potential":[13],"consequences.":[14],"Acoustic-based":[15],"convolutional":[16],"neural":[17],"(CNNs)":[19],"have":[20],"been":[21],"widely":[22],"employed":[23,106,138],"for":[24,85,148,195,227],"leak":[25,75,130,269],"identification,":[26],"leveraging":[27],"its":[28,51],"advantages":[29],"fast":[31],"processing":[32],"and":[33,60,121,125,160,170,180,241,252,265,276],"advanced":[34],"pattern":[35],"recognition":[36],"capabilities.":[37],"However,":[38],"CNN":[39],"exhibits":[40],"deficiency":[42],"interpretability,":[44],"which":[45],"hinders":[46],"comprehensive":[48],"understanding":[49],"of":[50,192,209,238],"decision-making":[52,236],"processes.":[53],"This":[54],"limitation":[55],"may":[56],"reduce":[57],"their":[58,129,145,274],"reliability":[59],"impede":[61],"further":[62],"improvements.":[63],"To":[64],"address":[65],"this":[66,68],"issue,":[67],"study":[69],"proposes":[70],"an":[71,260],"explainable":[72],"CNN-based":[73,112,268],"model":[77,202,240],"that":[78,178,200],"incorporates":[79],"gradient-weighted":[80],"class":[81],"activation":[82],"mapping":[83],"(Grad-CAM)":[84],"improved":[86],"interpretability.":[87,150,277],"For":[88],"data":[89,168],"collection,":[90],"acoustic":[91,267],"signals":[92,214],"were":[93,123,223],"collected":[94],"from":[95],"WDNs":[96],"Hong":[98],"Kong.":[99],"Besides,":[100],"variational":[101],"mode":[102],"decomposition":[103],"(VMD)":[104],"was":[105,137],"to":[107,143,212,263],"denoise":[108],"the":[109,140,156,201,206,224,235,239,243,256],"signals.":[110,229],"Three":[111],"models":[113,142,251],"[residual":[114],"network":[115],"(ResNet),":[116],"visual":[117],"geometry":[118],"group":[119],"(VGG),":[120],"AlexNet]":[122],"developed":[124,157],"assessed":[126],"based":[127],"on":[128,139,166,205,234],"performance.":[132],"After":[133],"training,":[134],"Grad-CAM":[135,174,193],"analysis":[136],"above":[141],"reveal":[144],"working":[146],"mechanism":[147],"better":[149],"The":[151,173],"results":[152,176,194],"demonstrate":[153],"that,":[154],"among":[155],"models,":[158,271],"AlexNet":[159],"VGG-19":[161,179],"demonstrated":[162],"superior":[163],"performance":[165],"testing":[167],"sets":[169],"out-of-sample":[171],"testing.":[172],"visualization":[175],"revealed":[177],"Grad-CAM\u2019s":[181],"attention":[182],"regions":[183],"effectively":[184],"captured":[185],"essential":[186],"signal":[187],"components.":[188],"Furthermore,":[189],"comparison":[191],"different":[196,249],"leakage":[197,253],"conditions":[198],"indicated":[199],"primarily":[203],"relied":[204],"frequency":[207,218,245],"components":[208,219],"750\u20131,250":[210],"Hz":[211,222],"classify":[213],"as":[215],"leaks,":[216],"while":[217],"below":[220],"500":[221],"primary":[225],"focus":[226],"noleak":[228],"These":[230],"insights":[231],"shed":[232],"light":[233],"process":[237],"highlighted":[242],"specific":[244],"bandwidth":[246],"associated":[247],"scenarios.":[254],"Overall,":[255],"proposed":[257],"method":[258],"offers":[259],"innovative":[261],"approach":[262],"enhance":[264],"explain":[266],"potentially":[272],"advancing":[273],"effectiveness":[275]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}