{"id":"https://openalex.org/W2604993202","doi":"https://doi.org/10.5430/air.v6n2p39","title":"Discrete event based hybrid framework for petroleum products pipeline activities classification","display_name":"Discrete event based hybrid framework for petroleum products pipeline activities classification","publication_year":2017,"publication_date":"2017-04-06","ids":{"openalex":"https://openalex.org/W2604993202","doi":"https://doi.org/10.5430/air.v6n2p39","mag":"2604993202"},"language":"en","primary_location":{"id":"doi:10.5430/air.v6n2p39","is_oa":true,"landing_page_url":"https://doi.org/10.5430/air.v6n2p39","pdf_url":"http://www.sciedu.ca/journal/index.php/air/article/download/9465/6956","source":{"id":"https://openalex.org/S4210167461","display_name":"Artificial Intelligence Research","issn_l":"1927-6974","issn":["1927-6974","1927-6982"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320842","host_organization_name":"Sciedu Press","host_organization_lineage":["https://openalex.org/P4310320842"],"host_organization_lineage_names":["Sciedu Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence Research","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"http://www.sciedu.ca/journal/index.php/air/article/download/9465/6956","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054957627","display_name":"Samuel S. Udoh","orcid":"https://orcid.org/0000-0001-9295-4052"},"institutions":[{"id":"https://openalex.org/I37797678","display_name":"University of Uyo","ror":"https://ror.org/0127mpp72","country_code":"NG","type":"education","lineage":["https://openalex.org/I37797678"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"S. S. Udoh","raw_affiliation_strings":["Department of Computer Science, Faculty of Science, University of Uyo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Faculty of Science, University of Uyo","institution_ids":["https://openalex.org/I37797678"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112411516","display_name":"Oluwole Charles Akinyokun","orcid":null},"institutions":[{"id":"https://openalex.org/I180664298","display_name":"Federal University of Technology","ror":"https://ror.org/01pvx8v81","country_code":"NG","type":"education","lineage":["https://openalex.org/I180664298"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"O. C. Akinyokun","raw_affiliation_strings":["Department of Computer Science, Faculty of Sciences, Federal University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Faculty of Sciences, Federal University of Technology","institution_ids":["https://openalex.org/I180664298"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050849127","display_name":"Udoinyang G. Inyang","orcid":"https://orcid.org/0000-0001-5086-303X"},"institutions":[{"id":"https://openalex.org/I37797678","display_name":"University of Uyo","ror":"https://ror.org/0127mpp72","country_code":"NG","type":"education","lineage":["https://openalex.org/I37797678"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"U. G. Inyang","raw_affiliation_strings":["Department of Computer Science, Faculty of Science, University of Uyo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Faculty of Science, University of Uyo","institution_ids":["https://openalex.org/I37797678"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028667529","display_name":"Oluwasanmi Olabode","orcid":"https://orcid.org/0000-0002-0538-7385"},"institutions":[{"id":"https://openalex.org/I180664298","display_name":"Federal University of Technology","ror":"https://ror.org/01pvx8v81","country_code":"NG","type":"education","lineage":["https://openalex.org/I180664298"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"O. Olabode","raw_affiliation_strings":["Department of Computer Science, Faculty of Sciences, Federal University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Faculty of Sciences, Federal University of Technology","institution_ids":["https://openalex.org/I180664298"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035146986","display_name":"Gabriel Babatunde Iwasokun","orcid":"https://orcid.org/0000-0002-9775-5631"},"institutions":[{"id":"https://openalex.org/I180664298","display_name":"Federal University of Technology","ror":"https://ror.org/01pvx8v81","country_code":"NG","type":"education","lineage":["https://openalex.org/I180664298"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"G. B. Iwasokun","raw_affiliation_strings":["Department of Computer Science, Faculty of Sciences, Federal University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Faculty of Sciences, Federal University of Technology","institution_ids":["https://openalex.org/I180664298"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2908,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.58261035,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"6","issue":"2","first_page":"39","last_page":"39"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13050","display_name":"Oil and Gas Production Techniques","score":0.9377999901771545,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T13050","display_name":"Oil and Gas Production Techniques","score":0.9377999901771545,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/devs","display_name":"DEVS","score":0.827904224395752},{"id":"https://openalex.org/keywords/adaptive-neuro-fuzzy-inference-system","display_name":"Adaptive neuro fuzzy inference system","score":0.8047100305557251},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6906998753547668},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6022905111312866},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4950329661369324},{"id":"https://openalex.org/keywords/hybrid-system","display_name":"Hybrid system","score":0.4857828915119171},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4385700821876526},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43670228123664856},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4073143005371094},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36720532178878784},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.29729679226875305},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.23134803771972656},{"id":"https://openalex.org/keywords/fuzzy-control-system","display_name":"Fuzzy control system","score":0.19829604029655457},{"id":"https://openalex.org/keywords/modeling-and-simulation","display_name":"Modeling and simulation","score":0.12898662686347961}],"concepts":[{"id":"https://openalex.org/C68757728","wikidata":"https://www.wikidata.org/wiki/Q911082","display_name":"DEVS","level":3,"score":0.827904224395752},{"id":"https://openalex.org/C186108316","wikidata":"https://www.wikidata.org/wiki/Q352530","display_name":"Adaptive neuro fuzzy inference system","level":4,"score":0.8047100305557251},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6906998753547668},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6022905111312866},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4950329661369324},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.4857828915119171},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4385700821876526},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43670228123664856},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4073143005371094},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36720532178878784},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.29729679226875305},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.23134803771972656},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.19829604029655457},{"id":"https://openalex.org/C167343916","wikidata":"https://www.wikidata.org/wiki/Q6888384","display_name":"Modeling and simulation","level":2,"score":0.12898662686347961},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5430/air.v6n2p39","is_oa":true,"landing_page_url":"https://doi.org/10.5430/air.v6n2p39","pdf_url":"http://www.sciedu.ca/journal/index.php/air/article/download/9465/6956","source":{"id":"https://openalex.org/S4210167461","display_name":"Artificial Intelligence Research","issn_l":"1927-6974","issn":["1927-6974","1927-6982"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320842","host_organization_name":"Sciedu Press","host_organization_lineage":["https://openalex.org/P4310320842"],"host_organization_lineage_names":["Sciedu Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence Research","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.5430/air.v6n2p39","is_oa":true,"landing_page_url":"https://doi.org/10.5430/air.v6n2p39","pdf_url":"http://www.sciedu.ca/journal/index.php/air/article/download/9465/6956","source":{"id":"https://openalex.org/S4210167461","display_name":"Artificial Intelligence Research","issn_l":"1927-6974","issn":["1927-6974","1927-6982"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320842","host_organization_name":"Sciedu Press","host_organization_lineage":["https://openalex.org/P4310320842"],"host_organization_lineage_names":["Sciedu Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence Research","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2604993202.pdf","grobid_xml":"https://content.openalex.org/works/W2604993202.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W365854946","https://openalex.org/W1027250026","https://openalex.org/W1154442760","https://openalex.org/W1157788930","https://openalex.org/W1494038024","https://openalex.org/W1548330136","https://openalex.org/W1857847907","https://openalex.org/W2001598892","https://openalex.org/W2044611148","https://openalex.org/W2061998517","https://openalex.org/W2081074218","https://openalex.org/W2089412873","https://openalex.org/W2105748885","https://openalex.org/W2113792315","https://openalex.org/W2156786022","https://openalex.org/W2161522742","https://openalex.org/W2164445311","https://openalex.org/W2166818060","https://openalex.org/W2245443546","https://openalex.org/W2608442539","https://openalex.org/W3036822033","https://openalex.org/W3105268672","https://openalex.org/W3188567101","https://openalex.org/W4232165342"],"related_works":["https://openalex.org/W2293708090","https://openalex.org/W2295011979","https://openalex.org/W4317792673","https://openalex.org/W2077935043","https://openalex.org/W1549331528","https://openalex.org/W2118500580","https://openalex.org/W2077533004","https://openalex.org/W1997417392","https://openalex.org/W1522872673","https://openalex.org/W4320063119"],"abstract_inverted_index":{"The":[0],"importance":[1],"of":[2,30,65,81,85,102,106,124,136,143,161,166,173,194,205],"timely":[3],"detection,":[4,189,201],"classification":[5,64,202],"and":[6,28,38,55,63,79,96,133,138,148,152,203],"response":[7],"to":[8,34,113,157],"anomalies":[9],"on":[10,32,67,104,176],"petroleum":[11],"products":[12],"pipeline":[13,125],"(PPP)":[14],"have":[15,99],"attracted":[16],"pragmatic":[17],"researches":[18],"in":[19,121,170,196],"recent":[20],"times.":[21],"There":[22],"is":[23],"need":[24],"for":[25,61,76,200],"efficient":[26],"monitoring":[27],"detection":[29,62,123],"activities":[31,66],"PPP":[33,206],"guide":[35],"leak":[36],"detections":[37,183],"remedy":[39],"decisions.":[40],"This":[41],"paper":[42],"develops":[43],"an":[44],"intelligent":[45],"hybrid":[46,128],"system,":[47],"driven":[48],"by":[49],"discrete":[50],"event":[51],"system":[52,59,175],"specification":[53],"(DEVS)":[54],"adaptive":[56],"neuro-fuzzy":[57],"inference":[58],"(ANFIS)":[60],"PPP.":[68,107],"A":[69,163],"dataset":[70],"comprising":[71],"330":[72],"records":[73],"was":[74,111,168],"used":[75],"training,":[77],"validation":[78],"testing":[80,134,164],"the":[82,117,122,146,149,159,171,197],"system.":[83],"Result":[84],"sensitivity":[86],"test":[87,178],"shows":[88],"that":[89],"inlet":[90,92,94],"pressure,":[91],"temperature,":[93],"volume":[95,98],"outlet":[97],"cumulative":[100],"significance":[101],"71.72%":[103],"flowrate":[105],"Hybrid":[108],"learning":[109,129],"algorithm":[110,120,130],"observed":[112,169],"converge":[114],"faster":[115],"than":[116],"back":[118],"propagation":[119],"activities.":[126,207],"ANFIS":[127],"with":[131,186],"training":[132],"errors":[135],"0.11980":[137],"0.010233":[139],"yielded":[140],"a":[141],"correlation":[142],"0.916":[144],"between":[145],"computed":[147],"desired":[150],"output":[151],"produced":[153],"optimal":[154],"consequent":[155],"parameters":[156],"boost":[158],"intelligence":[160],"DEVS.":[162],"error":[165],"0.0303":[167],"evaluation":[172],"DEVS-ANFIS":[174,198],"33":[177],"data":[179],"sample,":[180],"32":[181],"precise":[182],"were":[184],"made":[185],"one":[187],"incorrect":[188],"this":[190],"gives":[191],"96.97%":[192],"level":[193],"confidence":[195],"model":[199],"localization":[204]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}