{"id":"https://openalex.org/W1542219345","doi":"https://doi.org/10.1109/icmla.2004.1383501","title":"Feature fusion and degradation using self-organizing map","display_name":"Feature fusion and degradation using self-organizing map","publication_year":2005,"publication_date":"2005-04-06","ids":{"openalex":"https://openalex.org/W1542219345","doi":"https://doi.org/10.1109/icmla.2004.1383501","mag":"1542219345"},"language":"en","primary_location":{"id":"doi:10.1109/icmla.2004.1383501","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla.2004.1383501","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 International Conference on Machine Learning and Applications, 2004. Proceedings.","raw_type":"proceedings-article"},"type":"conference-paper","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/A5097904114","display_name":"Hai Qui","orcid":null},"institutions":[{"id":"https://openalex.org/I43579087","display_name":"University of Wisconsin\u2013Milwaukee","ror":"https://ror.org/031q21x57","country_code":"US","type":"education","lineage":["https://openalex.org/I43579087"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hai Qui","raw_affiliation_strings":["NSF Center for Intelligent Maintenance Systems (IMS), Department of Industrial and Manufacturing Engineering, University of Wisconsin-Milwaukee, 9100N Swan Road Milwaukee, WI 53224"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NSF Center for Intelligent Maintenance Systems (IMS), Department of Industrial and Manufacturing Engineering, University of Wisconsin-Milwaukee, 9100N Swan Road Milwaukee, WI 53224","institution_ids":["https://openalex.org/I43579087"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108499778","display_name":"J. Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I43579087","display_name":"University of Wisconsin\u2013Milwaukee","ror":"https://ror.org/031q21x57","country_code":"US","type":"education","lineage":["https://openalex.org/I43579087"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. Lee","raw_affiliation_strings":["Department of Industrial and Manufacturing Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial and Manufacturing Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI, USA","institution_ids":["https://openalex.org/I43579087"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I43579087"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.05877787,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"96","issue":null,"first_page":"107","last_page":"114"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11062","display_name":"Gear and Bearing Dynamics Analysis","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10876","display_name":"Fault Detection and Control Systems","score":0.9799000024795532,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/prognostics","display_name":"Prognostics","score":0.8069210052490234},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.642326831817627},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5746793746948242},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.553578794002533},{"id":"https://openalex.org/keywords/degradation","display_name":"Degradation (telecommunications)","score":0.5484760403633118},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5452171564102173},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5378526449203491},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5266625285148621},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.515191912651062},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4692259728908539},{"id":"https://openalex.org/keywords/condition-monitoring","display_name":"Condition monitoring","score":0.46578043699264526},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2488868534564972}],"concepts":[{"id":"https://openalex.org/C129364497","wikidata":"https://www.wikidata.org/wiki/Q3042561","display_name":"Prognostics","level":2,"score":0.8069210052490234},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.642326831817627},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5746793746948242},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.553578794002533},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.5484760403633118},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5452171564102173},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5378526449203491},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5266625285148621},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.515191912651062},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4692259728908539},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.46578043699264526},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2488868534564972},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmla.2004.1383501","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla.2004.1383501","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 International Conference on Machine Learning and Applications, 2004. Proceedings.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"id":"https://metadata.un.org/sdg/12","display_name":"Responsible consumption and production"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1544577158","https://openalex.org/W1679913846","https://openalex.org/W1964136459","https://openalex.org/W1970644055","https://openalex.org/W1974543974","https://openalex.org/W1987834744","https://openalex.org/W1995927766","https://openalex.org/W2024760831","https://openalex.org/W2051861458","https://openalex.org/W2052006079","https://openalex.org/W2097439569","https://openalex.org/W2116651418","https://openalex.org/W2142332339","https://openalex.org/W2313953460","https://openalex.org/W2489292218","https://openalex.org/W2798401351","https://openalex.org/W3036846224","https://openalex.org/W4213332169","https://openalex.org/W4253708194","https://openalex.org/W6750353007","https://openalex.org/W6779887223"],"related_works":["https://openalex.org/W2310476526","https://openalex.org/W2908973203","https://openalex.org/W2801712269","https://openalex.org/W1872896676","https://openalex.org/W2156691445","https://openalex.org/W2045186954","https://openalex.org/W3000986292","https://openalex.org/W1502469213","https://openalex.org/W2123638926","https://openalex.org/W2568310397"],"abstract_inverted_index":{"Successful":[0],"prognostics":[1,35],"is":[2,15,44,70,103,129,154],"based":[3,68],"on":[4],"effective":[5],"feature":[6,10,37,49,80],"exaction":[7],"and":[8,23,34,82,112,150],"correct":[9],"selection":[11],"processes.":[12],"Feature":[13],"map":[14],"one":[16],"of":[17,76,79,119,124,136,170],"the":[18,30,55,74,77,100,121,125,147,157,168,171],"widely":[19],"used":[20],"performance":[21,110,152],"assessment":[22,111,153],"degradation":[24,32,56,83,96,113],"detection":[25,33,114,141],"methods.":[26],"By":[27],"continuously":[28],"tracking":[29],"trajectories,":[31],"in":[36],"space":[38,50,81],"can":[39,52,142],"be":[40,143],"conducted.":[41],"The":[42,105],"challenge":[43],"how":[45],"to":[46,72,91,131],"construct":[47],"a":[48,61,117,133],"that":[51,108],"consistently":[53],"exemplify":[54],"pattern.":[57],"In":[58],"this":[59],"paper,":[60],"Self":[62],"Organizing":[63],"Map":[64],"(SOM)":[65],"neural":[66],"network":[67],"method":[69,102],"proposed":[71,101],"address":[73],"problem":[75],"construction":[78],"detection.":[84],"Roller":[85],"bearing":[86,173],"run-to-failure":[87],"tests":[88],"are":[89],"conducted":[90],"generate":[92],"full":[93],"life":[94],"cycle":[95],"data,":[97],"by":[98,145,156],"which":[99],"validated.":[104],"results":[106],"demonstrate":[107],"SOM-based":[109],"approach":[115],"provides":[116,164],"means":[118],"enhancing":[120],"condition":[122],"monitoring":[123,146],"roller":[126],"bearing.":[127],"It":[128,163],"able":[130],"provide":[132],"comprehensible":[134],"indication":[135],"current":[137],"operation":[138],"state.":[139],"Degradation":[140],"fulfilled":[144],"trajectories.":[148],"Robust":[149],"quantitative":[151],"achieved":[155],"Minimum":[158],"Quantization":[159],"Error":[160],"(MQE)":[161],"calculation.":[162],"solid":[165],"foundation":[166],"for":[167],"development":[169],"rolling":[172],"prognostic":[174],"method.":[175]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
