{"id":"https://openalex.org/W4408314304","doi":"https://doi.org/10.32604/cmc.2025.061062","title":"An Explainable Autoencoder-Based Feature Extraction Combined with CNN-LSTM-PSO Model for Improved Predictive Maintenance","display_name":"An Explainable Autoencoder-Based Feature Extraction Combined with CNN-LSTM-PSO Model for Improved Predictive Maintenance","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4408314304","doi":"https://doi.org/10.32604/cmc.2025.061062"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.061062","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.061062","pdf_url":"https://cdn.techscience.press/files/cmc/2025/TSP_CMC-83-1/TSP_CMC_61062/TSP_CMC_61062.pdf","source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://cdn.techscience.press/files/cmc/2025/TSP_CMC-83-1/TSP_CMC_61062/TSP_CMC_61062.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061139051","display_name":"Ishaani Priyadarshini","orcid":"https://orcid.org/0000-0002-8826-8065"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ishaani Priyadarshini","raw_affiliation_strings":["eCornell , Division of Online Learning , Cornell University , Ithaca , NY 14850 , USA"],"affiliations":[{"raw_affiliation_string":"eCornell , Division of Online Learning , Cornell University , Ithaca , NY 14850 , USA","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5061139051"],"corresponding_institution_ids":["https://openalex.org/I205783295"],"apc_list":null,"apc_paid":null,"fwci":18.4785,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.98580346,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"83","issue":"1","first_page":"635","last_page":"659"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14280","display_name":"Big Data Technologies and Applications","score":0.4876999855041504,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T14280","display_name":"Big Data Technologies and Applications","score":0.4876999855041504,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.48420000076293945,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T13832","display_name":"Advanced Decision-Making Techniques","score":0.4431999921798706,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.8171745538711548},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.680391252040863},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6712749004364014},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.548600971698761},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5457744598388672},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45625337958335876},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3460671901702881},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.19784054160118103}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8171745538711548},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.680391252040863},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6712749004364014},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.548600971698761},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5457744598388672},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45625337958335876},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3460671901702881},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.19784054160118103},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.061062","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.061062","pdf_url":"https://cdn.techscience.press/files/cmc/2025/TSP_CMC-83-1/TSP_CMC_61062/TSP_CMC_61062.pdf","source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.061062","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.061062","pdf_url":"https://cdn.techscience.press/files/cmc/2025/TSP_CMC-83-1/TSP_CMC_61062/TSP_CMC_61062.pdf","source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4408314304.pdf","grobid_xml":"https://content.openalex.org/works/W4408314304.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W4318040555","https://openalex.org/W4386248484","https://openalex.org/W4387339066","https://openalex.org/W4387492920","https://openalex.org/W4388090033","https://openalex.org/W4388260481","https://openalex.org/W4388742887","https://openalex.org/W4389110067","https://openalex.org/W4390602118","https://openalex.org/W4391055393","https://openalex.org/W4391547839","https://openalex.org/W4391744632","https://openalex.org/W4391855182","https://openalex.org/W4392137185","https://openalex.org/W4399467983","https://openalex.org/W4399705962","https://openalex.org/W4399713343","https://openalex.org/W4400020165","https://openalex.org/W4403817196","https://openalex.org/W4403934140","https://openalex.org/W4406606313"],"related_works":["https://openalex.org/W2601157893","https://openalex.org/W2373006798","https://openalex.org/W2131735617","https://openalex.org/W2056912418","https://openalex.org/W2033213769","https://openalex.org/W4312376745","https://openalex.org/W2136016640","https://openalex.org/W2049538278","https://openalex.org/W2886173746","https://openalex.org/W4200043248"],"abstract_inverted_index":{"Predictive":[0],"maintenance":[1,20],"plays":[2],"a":[3],"crucial":[4],"role":[5],"in":[6,14,25],"preventing":[7],"equipment":[8],"failures":[9],"and":[10,32],"minimizing":[11],"operational":[12],"downtime":[13],"modern":[15],"industries.":[16],"However,":[17],"traditional":[18],"predictive":[19],"methods":[21],"often":[22],"face":[23],"challenges":[24],"adapting":[26],"to":[27],"d...":[28],"|":[29],"Find,":[30],"read":[31],"cite":[33],"all":[34],"the":[35],"research":[36],"you":[37],"need":[38],"on":[39],"Tech":[40],"Science":[41],"Press":[42]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-08T06:56:09.383167","created_date":"2025-10-10T00:00:00"}