{"id":"https://openalex.org/W2156786022","doi":"https://doi.org/10.5430/air.v3n4p77","title":"A hybrid knowledge discovery system for oil spillage risks pattern classification","display_name":"A hybrid knowledge discovery system for oil spillage risks pattern classification","publication_year":2014,"publication_date":"2014-11-03","ids":{"openalex":"https://openalex.org/W2156786022","doi":"https://doi.org/10.5430/air.v3n4p77","mag":"2156786022"},"language":"en","primary_location":{"id":"doi:10.5430/air.v3n4p77","is_oa":true,"landing_page_url":"https://doi.org/10.5430/air.v3n4p77","pdf_url":"http://www.sciedu.ca/journal/index.php/air/article/download/5252/3478","source":{"id":"https://openalex.org/S4210167461","display_name":"Artificial Intelligence Research","issn_l":"1927-6974","issn":["1927-6974","1927-6982"],"is_oa":false,"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":"bronze","oa_url":"http://www.sciedu.ca/journal/index.php/air/article/download/5252/3478","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Udoinyang Godwin Inyang","orcid":null},"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":"Udoinyang Godwin Inyang","raw_affiliation_strings":["Department of Computer Science, Faculty of Science, University of Uyo, Uyo, Nigeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Faculty of Science, University of Uyo, Uyo, Nigeria","institution_ids":["https://openalex.org/I37797678"]}]},{"author_position":"last","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":"Oluwole Charles Akinyokun","raw_affiliation_strings":["Department of Computer Science, Federal University of Technology, Akure,  Nigeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Federal University of Technology, Akure,  Nigeria","institution_ids":["https://openalex.org/I180664298"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7756,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.72992889,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"3","issue":"4","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12316","display_name":"Oil Spill Detection and Mitigation","score":0.964900016784668,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12316","display_name":"Oil Spill Detection and Mitigation","score":0.964900016784668,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.9646000266075134,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/adaptive-neuro-fuzzy-inference-system","display_name":"Adaptive neuro fuzzy inference system","score":0.7725120782852173},{"id":"https://openalex.org/keywords/spillage","display_name":"Spillage","score":0.7480741739273071},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5932993292808533},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5777820348739624},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5300903916358948},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5181525945663452},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4920015037059784},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4244175851345062},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4208943247795105},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4202454686164856},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.33739882707595825},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2214687466621399},{"id":"https://openalex.org/keywords/fuzzy-control-system","display_name":"Fuzzy control system","score":0.16871538758277893}],"concepts":[{"id":"https://openalex.org/C186108316","wikidata":"https://www.wikidata.org/wiki/Q352530","display_name":"Adaptive neuro fuzzy inference system","level":4,"score":0.7725120782852173},{"id":"https://openalex.org/C2779640004","wikidata":"https://www.wikidata.org/wiki/Q16979462","display_name":"Spillage","level":2,"score":0.7480741739273071},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5932993292808533},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5777820348739624},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5300903916358948},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5181525945663452},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4920015037059784},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4244175851345062},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4208943247795105},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4202454686164856},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.33739882707595825},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2214687466621399},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.16871538758277893},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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},{"id":"https://openalex.org/C548081761","wikidata":"https://www.wikidata.org/wiki/Q180388","display_name":"Waste management","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5430/air.v3n4p77","is_oa":true,"landing_page_url":"https://doi.org/10.5430/air.v3n4p77","pdf_url":"http://www.sciedu.ca/journal/index.php/air/article/download/5252/3478","source":{"id":"https://openalex.org/S4210167461","display_name":"Artificial Intelligence Research","issn_l":"1927-6974","issn":["1927-6974","1927-6982"],"is_oa":false,"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.v3n4p77","is_oa":true,"landing_page_url":"https://doi.org/10.5430/air.v3n4p77","pdf_url":"http://www.sciedu.ca/journal/index.php/air/article/download/5252/3478","source":{"id":"https://openalex.org/S4210167461","display_name":"Artificial Intelligence Research","issn_l":"1927-6974","issn":["1927-6974","1927-6982"],"is_oa":false,"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/W2156786022.pdf","grobid_xml":"https://content.openalex.org/works/W2156786022.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W44465109","https://openalex.org/W124008658","https://openalex.org/W1506285740","https://openalex.org/W1528140509","https://openalex.org/W1558625765","https://openalex.org/W1584715075","https://openalex.org/W1604905867","https://openalex.org/W1787564306","https://openalex.org/W1971078475","https://openalex.org/W1973036367","https://openalex.org/W1983188045","https://openalex.org/W2016210396","https://openalex.org/W2044611148","https://openalex.org/W2045506233","https://openalex.org/W2048835245","https://openalex.org/W2074253074","https://openalex.org/W2082381069","https://openalex.org/W2094978308","https://openalex.org/W2097571405","https://openalex.org/W2099560096","https://openalex.org/W2102148524","https://openalex.org/W2103414828","https://openalex.org/W2116003303","https://openalex.org/W2116996317","https://openalex.org/W2133321814","https://openalex.org/W2137984277","https://openalex.org/W2139839769","https://openalex.org/W2152150600","https://openalex.org/W2156746760","https://openalex.org/W2158366037","https://openalex.org/W2161132479","https://openalex.org/W2166853020","https://openalex.org/W2166908377","https://openalex.org/W2172186225","https://openalex.org/W2181556800","https://openalex.org/W2284148283","https://openalex.org/W2892004002","https://openalex.org/W2912940014","https://openalex.org/W3011460294","https://openalex.org/W3023540311","https://openalex.org/W4205391292","https://openalex.org/W4205741445","https://openalex.org/W4229612460","https://openalex.org/W4238262401","https://openalex.org/W4243694527","https://openalex.org/W4285719527","https://openalex.org/W4301971222","https://openalex.org/W6601998182","https://openalex.org/W6605069247"],"related_works":["https://openalex.org/W2261928542","https://openalex.org/W2384014964","https://openalex.org/W2254300685","https://openalex.org/W250986124","https://openalex.org/W2393295287","https://openalex.org/W2915015943","https://openalex.org/W3157118002","https://openalex.org/W4391666029","https://openalex.org/W2071875271","https://openalex.org/W2952374685"],"abstract_inverted_index":{"The":[0,111,158,176,198,233],"complexity":[1],"and":[2,13,32,59,75,123,150,155,173,214,223,230,247],"the":[3,28,56,78,161,182,203,212,226,245],"dynamism":[4],"of":[5,27,61,68,77,81,89,95,99,116,160,169,216,225,249],"oil":[6,62,91,217,250],"spillages":[7],"make":[8],"it":[9],"difficult":[10],"for":[11,24,55,72,211],"planners":[12],"responders":[14],"to":[15,35],"produce":[16],"robust":[17],"plans":[18],"towardstheir":[19],"management.":[20],"There":[21],"is":[22,119,228],"need":[23],"an":[25,43],"understanding":[26],"nature,":[29],"sources,":[30],"impact":[31],"responses":[33],"required":[34],"prevent":[36],"or":[37],"controltheir":[38],"occurrence.":[39],"This":[40],"paper":[41,204],"develops":[42],"intelligent":[44],"hybrid":[45,108,208],"system":[46],"driven":[47],"by":[48],"Sugeno-Type":[49],"Adaptive":[50],"Neuro":[51],"Fuzzy":[52],"InferenceSystem":[53],"(ANFIS)":[54],"identification,":[57],"extraction":[58],"classification":[60,215,248],"spillage":[63,218,251],"risk":[64,219,252],"patterns.":[65,220,253],"Dataset":[66],"consisting":[67],"1008records":[69],"was":[70,145,163],"used":[71],"training,":[73],"validation":[74],"testing":[76,124],"system.":[79],"Result":[80],"sensitivity":[82],"analysis":[83],"shows":[84],"that":[85,238],"Cause,":[86],"Locationand":[87],"Type":[88],"spilled":[90],"have":[92],"cumulative":[93],"significance":[94],"85.1%.":[96],"Optimal":[97],"weights":[98],"Neural":[100],"Network":[101],"(NN)":[102],"were":[103],"determined":[104],"viaGenetic":[105],"Algorithm":[106],"with":[107,147,165,178],"encoding":[109],"scheme.":[110],"Mean":[112],"Squared":[113],"Error":[114],"(MSE)":[115],"NN":[117,121],"training":[118,222],"0.2405.":[120],"training,validation":[122],"results":[125,236,243],"yielded":[126],"R":[127],"&gt;":[128],"0.839":[129],"in":[130,202,244],"all":[131,186],"cases":[132],"indicating":[133],"a":[134],"strong":[135],"linear":[136],"relationship":[137],"between":[138],"each":[139],"output":[140],"andtarget":[141],"data.":[142],"Rule":[143],"pruning":[144],"performed":[146,192],"support":[148],"(15%)":[149],"confidence":[151],"(10%)":[152],"minimum":[153],"thresholds":[154],"antecedent-size":[156],"of3.":[157],"performance":[159,184],"ANFIS":[162,199,239],"evaluated":[164],"eight":[166],"different":[167],"types":[168],"membership":[170],"functions":[171],"(MFs)":[172],"two":[174],"learningalgorithms.":[175],"model":[177,200,227],"triangular":[179,206],"MF":[180],"gave":[181],"best":[183],"among":[185],"other":[187],"given":[188],"models":[189],"while":[190],"hybrid-learningalgorithm":[191],"better":[193],"than":[194],"back":[195],"propagation":[196],"algorithm.":[197],"reported":[201],"adopted":[205],"MFand":[207],"learning":[209],"algorithm":[210],"predication":[213],"Average":[221],"testingMSE":[224],"0.414315":[229],"0.221402":[231],"respectively.":[232],"knowledge":[234],"mining":[235],"show":[237],"based":[240],"systemsprovide":[241],"satisfactory":[242],"prediction":[246]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
