{"id":"https://openalex.org/W4296070925","doi":"https://doi.org/10.14428/esann/2022.es2022-59","title":"Simple Non Regressive Informed Machine Learning Model for Predictive Maintenance of Railway Critical Assets","display_name":"Simple Non Regressive Informed Machine Learning Model for Predictive Maintenance of Railway Critical Assets","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4296070925","doi":"https://doi.org/10.14428/esann/2022.es2022-59"},"language":"en","primary_location":{"id":"doi:10.14428/esann/2022.es2022-59","is_oa":true,"landing_page_url":"http://doi.org/10.14428/esann/2022.es2022-59","pdf_url":"https://doi.org/10.14428/esann/2022.es2022-59","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESANN 2022 proceedings","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.14428/esann/2022.es2022-59","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045802198","display_name":"Luca Oneto","orcid":"https://orcid.org/0000-0002-8445-395X"},"institutions":[{"id":"https://openalex.org/I83816512","display_name":"University of Genoa","ror":"https://ror.org/0107c5v14","country_code":"IT","type":"education","lineage":["https://openalex.org/I83816512"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luca Oneto","raw_affiliation_strings":["University of Genoa, Via Opera Pia 11a, 16145, Genova, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Genoa, Via Opera Pia 11a, 16145, Genova, Italy","institution_ids":["https://openalex.org/I83816512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033914706","display_name":"Simone Minisi","orcid":"https://orcid.org/0000-0003-2351-6715"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Simone Minisi","raw_affiliation_strings":["ZenaByte s.r.l., Via Cesarea 2, 16121, Genova, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ZenaByte s.r.l., Via Cesarea 2, 16121, Genova, Italy","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000193693","display_name":"Andrea Garrone","orcid":null},"institutions":[{"id":"https://openalex.org/I83816512","display_name":"University of Genoa","ror":"https://ror.org/0107c5v14","country_code":"IT","type":"education","lineage":["https://openalex.org/I83816512"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Andrea Garrone","raw_affiliation_strings":["University of Genoa, Via Opera Pia 11a, 16145, Genova, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Genoa, Via Opera Pia 11a, 16145, Genova, Italy","institution_ids":["https://openalex.org/I83816512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087959776","display_name":"Renzo Canepa","orcid":null},"institutions":[{"id":"https://openalex.org/I4210117345","display_name":"Trenitalia (Italy)","ror":"https://ror.org/02c4sht73","country_code":"IT","type":"company","lineage":["https://openalex.org/I4210117345"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Renzo Canepa","raw_affiliation_strings":["Rete Ferroviaria Italiana, Via Don Vincenzo Minetti 6/5, 16126, Genova, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rete Ferroviaria Italiana, Via Don Vincenzo Minetti 6/5, 16126, Genova, Italy","institution_ids":["https://openalex.org/I4210117345"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048451072","display_name":"Carlo Dambra","orcid":"https://orcid.org/0000-0002-4375-5441"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carlo Dambra","raw_affiliation_strings":["ZenaByte s.r.l., Via Cesarea 2, 16121, Genova, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ZenaByte s.r.l., Via Cesarea 2, 16121, Genova, Italy","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036611143","display_name":"Davide Anguita","orcid":"https://orcid.org/0000-0001-7523-5291"},"institutions":[{"id":"https://openalex.org/I83816512","display_name":"University of Genoa","ror":"https://ror.org/0107c5v14","country_code":"IT","type":"education","lineage":["https://openalex.org/I83816512"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Davide Anguita","raw_affiliation_strings":["University of Genoa, Via Opera Pia 11a, 16145, Genova, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Genoa, Via Opera Pia 11a, 16145, Genova, Italy","institution_ids":["https://openalex.org/I83816512"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1214,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.42265257,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"133","last_page":"138"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14420","display_name":"Advanced Research in Systems and Signal Processing","score":0.8069999814033508,"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/T14420","display_name":"Advanced Research in Systems and Signal Processing","score":0.8069999814033508,"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/T13891","display_name":"Engineering Diagnostics and Reliability","score":0.7929999828338623,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/pipeline-transport","display_name":"Pipeline transport","score":0.5702000260353088},{"id":"https://openalex.org/keywords/predictive-maintenance","display_name":"Predictive maintenance","score":0.5519999861717224},{"id":"https://openalex.org/keywords/asset","display_name":"Asset (computer security)","score":0.5062999725341797},{"id":"https://openalex.org/keywords/asset-management","display_name":"Asset management","score":0.4408999979496002},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.4359000027179718},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4296000003814697},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.41830000281333923},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.4018000066280365},{"id":"https://openalex.org/keywords/track","display_name":"Track (disk drive)","score":0.39469999074935913}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6155999898910522},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.5702000260353088},{"id":"https://openalex.org/C70452415","wikidata":"https://www.wikidata.org/wiki/Q3182448","display_name":"Predictive maintenance","level":2,"score":0.5519999861717224},{"id":"https://openalex.org/C76178495","wikidata":"https://www.wikidata.org/wiki/Q4808784","display_name":"Asset (computer security)","level":2,"score":0.5062999725341797},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48339998722076416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4422999918460846},{"id":"https://openalex.org/C2776517139","wikidata":"https://www.wikidata.org/wiki/Q873442","display_name":"Asset management","level":2,"score":0.4408999979496002},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.4359000027179718},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4296000003814697},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.41830000281333923},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.4018000066280365},{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.39469999074935913},{"id":"https://openalex.org/C24090081","wikidata":"https://www.wikidata.org/wiki/Q1043452","display_name":"Preventive maintenance","level":2,"score":0.36250001192092896},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.33799999952316284},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.30410000681877136},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.296099990606308},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2687999904155731},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C2779119184","wikidata":"https://www.wikidata.org/wiki/Q294350","display_name":"ALARM","level":2,"score":0.25450000166893005},{"id":"https://openalex.org/C33499554","wikidata":"https://www.wikidata.org/wiki/Q1417134","display_name":"Dashboard","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14428/esann/2022.es2022-59","is_oa":true,"landing_page_url":"http://doi.org/10.14428/esann/2022.es2022-59","pdf_url":"https://doi.org/10.14428/esann/2022.es2022-59","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESANN 2022 proceedings","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.14428/esann/2022.es2022-59","is_oa":true,"landing_page_url":"http://doi.org/10.14428/esann/2022.es2022-59","pdf_url":"https://doi.org/10.14428/esann/2022.es2022-59","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESANN 2022 proceedings","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G249577440","display_name":"Development of prescriptive AnalYtics baseD on aRtificial intElligence for iAMS","funder_award_id":"101008913","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G2607367172","display_name":"Intelligent Innovative Smart Maintenance of Assets by integRated Technologies 2","funder_award_id":"881574","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G7842005466","display_name":null,"funder_award_id":"Horizon 2020","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G7931553538","display_name":null,"funder_award_id":"Shift2Rail","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4296070925.pdf","grobid_xml":"https://content.openalex.org/works/W4296070925.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W607505555","https://openalex.org/W2148603752","https://openalex.org/W2166262949","https://openalex.org/W2189162242","https://openalex.org/W2295598076","https://openalex.org/W2317435920","https://openalex.org/W2963015369","https://openalex.org/W3006087551","https://openalex.org/W3103972686","https://openalex.org/W3178138002","https://openalex.org/W3178436058","https://openalex.org/W4205436505","https://openalex.org/W4293246336","https://openalex.org/W6795489260"],"related_works":["https://openalex.org/W18977309","https://openalex.org/W2366600750","https://openalex.org/W2889453578","https://openalex.org/W4200275256","https://openalex.org/W3154094704","https://openalex.org/W86096423","https://openalex.org/W3159087789","https://openalex.org/W2046446391","https://openalex.org/W2623682848","https://openalex.org/W3098095456"],"abstract_inverted_index":{"Signals,":[0],"track":[1],"circuits,":[2],"switches,":[3],"and":[4,12,65,117],"relay":[5],"rooms":[6],"are":[7],"simultaneously":[8],"the":[9,27,34,46,99,128,157,171],"most":[10,13],"critical":[11],"maintained":[14,95],"railway":[15,28],"assets.":[16],"A":[17],"fault":[18],"of":[19,21,69,127,131],"one":[20,126],"these":[22,132],"assets":[23,39],"may":[24,40],"strongly":[25],"reduce":[26],"network":[29],"capacity":[30],"or":[31],"even":[32],"disrupt":[33],"circulation.":[35],"Effectively":[36],"predicting":[37,149],"what":[38,90],"need":[41,92],"maintenance":[42],"allows":[43],"to":[44,87,93,135],"anticipate":[45],"intervention":[47],"thus":[48],"avoiding":[49],"a":[50,78,120],"failure.":[51],"Currently,":[52],"this":[53,74,163,167],"problem":[54,168],"is":[55,134],"tackled":[56],"by":[57,156,169],"infrastructure":[58],"managers":[59],"mostly":[60],"relying":[61],"on":[62,98,179],"operators'":[63],"experience":[64],"with":[66,174],"limited":[67],"support":[68],"decision":[70],"supporting":[71],"tools.":[72],"In":[73,124,162],"paper,":[75],"we":[76,165],"propose":[77],"Simple":[79],"Informed":[80],"Machine":[81],"Learning":[82],"(ML)":[83],"based":[84],"model":[85,114,159],"able":[86],"automatically":[88],"predict":[89],"asset":[91],"be":[94,137],"fully":[96],"leveraging":[97],"operator":[100],"experience.":[101],"However,":[102],"ML":[103,173],"models":[104],"in":[105],"modern":[106],"industrial":[107],"MLOps":[108],"pipelines":[109,133],"demand":[110],"continuous":[111],"data":[112,181],"collection,":[113],"re-training,":[115],"testing,":[116],"monitoring,":[118],"creating":[119],"large":[121],"technical":[122],"debt.":[123],"fact,":[125],"main":[129],"requirements":[130],"not":[136,140,147],"regressive,":[138],"i.e.,":[139],"simply":[141],"improve":[142],"average":[143],"performances":[144],"but":[145],"also":[146],"incorrectly":[148],"an":[150],"output":[151],"that":[152],"was":[153],"correctly":[154],"classified":[155],"reference":[158],"(negative":[160],"flips).":[161],"work":[164],"face":[166],"empowering":[170],"proposed":[172],"Non":[175],"Regressive":[176],"properties.":[177],"Results":[178],"real":[180],"coming":[182]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-16T09:24:06.705377","created_date":"2025-10-10T00:00:00"}
