{"id":"https://openalex.org/W3090497929","doi":"https://doi.org/10.1109/ccta41146.2020.9206293","title":"A Performance Comparison of LSTM and Recursive SID Methods in Thermal Modeling of Implantable Medical Devices","display_name":"A Performance Comparison of LSTM and Recursive SID Methods in Thermal Modeling of Implantable Medical Devices","publication_year":2020,"publication_date":"2020-08-01","ids":{"openalex":"https://openalex.org/W3090497929","doi":"https://doi.org/10.1109/ccta41146.2020.9206293","mag":"3090497929"},"language":"en","primary_location":{"id":"doi:10.1109/ccta41146.2020.9206293","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccta41146.2020.9206293","pdf_url":null,"source":{"id":"https://openalex.org/S4306498667","display_name":"2020 IEEE Conference on Control Technology and Applications (CCTA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Conference on Control Technology and Applications (CCTA)","raw_type":"proceedings-article"},"type":"article","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/A5016367092","display_name":"Ayca Ermis","orcid":"https://orcid.org/0000-0002-3969-8640"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ayca Ermis","raw_affiliation_strings":["School of ECE Georgia Tech Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"School of ECE Georgia Tech Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101679850","display_name":"Mi Zhou","orcid":"https://orcid.org/0000-0001-8469-5361"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mi Zhou","raw_affiliation_strings":["School of ECE Georgia Tech Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"School of ECE Georgia Tech Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074186813","display_name":"Yen-Pang Lai","orcid":"https://orcid.org/0000-0001-5598-1756"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yen-Pang Lai","raw_affiliation_strings":["School of ECE Georgia Tech Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"School of ECE Georgia Tech Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100386001","display_name":"Ying Zhang","orcid":"https://orcid.org/0000-0001-5246-2141"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ying Zhang","raw_affiliation_strings":["School of ECE Georgia Tech Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"School of ECE Georgia Tech Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5016367092"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.4,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":null,"first_page":"776","last_page":"781"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11749","display_name":"Iterative Learning Control Systems","score":0.9776999950408936,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.9740999937057495,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7169574499130249},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.7154775857925415},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5912188291549683},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5472861528396606},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.491356760263443},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.4755920171737671},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12004941701889038}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7169574499130249},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.7154775857925415},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5912188291549683},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5472861528396606},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.491356760263443},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.4755920171737671},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12004941701889038},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccta41146.2020.9206293","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccta41146.2020.9206293","pdf_url":null,"source":{"id":"https://openalex.org/S4306498667","display_name":"2020 IEEE Conference on Control Technology and Applications (CCTA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Conference on Control Technology and Applications (CCTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1008315879","https://openalex.org/W1974206351","https://openalex.org/W1981860553","https://openalex.org/W1988115241","https://openalex.org/W1997184856","https://openalex.org/W1998242475","https://openalex.org/W2015798237","https://openalex.org/W2064675550","https://openalex.org/W2096424603","https://openalex.org/W2164789990","https://openalex.org/W2735778951","https://openalex.org/W2900103594","https://openalex.org/W2905770204","https://openalex.org/W2946349917","https://openalex.org/W2955963731","https://openalex.org/W2994306103","https://openalex.org/W3045006783","https://openalex.org/W4243455742","https://openalex.org/W4249062517","https://openalex.org/W6781205450"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2102148524","https://openalex.org/W2053286651","https://openalex.org/W2181743346","https://openalex.org/W2187401768","https://openalex.org/W2181413294","https://openalex.org/W2314720829","https://openalex.org/W2989452537","https://openalex.org/W2052122378"],"abstract_inverted_index":{"This":[0],"paper":[1,32],"investigates":[2],"application":[3],"of":[4,20,37,44,68,75,87,109,146,166],"long":[5],"short-term":[6],"memory":[7],"(LSTM)":[8],"and":[9,66,96,112,127],"recursive":[10],"system":[11,111],"identification":[12],"(RSID)":[13],"algorithms":[14,28],"to":[15,124,180],"predict":[16,33,105],"the":[17,34,80,88,101,106,110,114,131,139,144,147,151,160,164,167,174],"thermal":[18,107],"dynamics":[19,108],"bio-implants,":[21],"e.g.":[22],"UEA":[23],"under":[24],"certain":[25,118],"assumptions.":[26],"Both":[27,94],"implemented":[29],"in":[30,49,58,128,142,150],"this":[31],"temperature":[35],"readings":[36],"heat":[38],"sensors":[39],"using":[40,56],"a":[41],"window":[42],"size":[43],"10":[45],"data":[46],"points.":[47],"Simulations":[48],"COMSOL":[50,125],"software":[51],"as":[52,54],"well":[53],"experiments":[55],"an":[57],"vitro":[59,129],"experimental":[60,97],"systems":[61],"are":[62],"utilized":[63],"for":[64,92,120,138,176],"validation":[65],"comparison":[67],"algorithm":[69,82,91,116,133,153,169],"performances.":[70],"Mean":[71],"squared":[72],"error":[73],"(MSE)":[74],"prediction":[76],"results":[77,98],"based":[78],"on":[79],"LSTM":[81,102,132,175],"is":[83,154,170],"compared":[84],"against":[85],"that":[86,100],"competitive":[89],"RSID":[90,115,152,168],"evaluation.":[93],"simulation":[95],"indicate":[99],"can":[103],"accurately":[104],"outperforms":[113],"when":[117],"conditions":[119],"inputs":[121],"hold.":[122],"According":[123],"simulations":[126],"experiments,":[130],"returns":[134],"more":[135],"reliable":[136],"predictions":[137],"time":[140],"period":[141],"which":[143],"convergence":[145],"adaptive":[148,161,182],"filters":[149,162],"not":[155],"yet":[156],"achieved.":[157],"Alternatively,":[158],"once":[159],"converge,":[163],"performance":[165],"significantly":[171],"better":[172],"than":[173],"some":[177],"cases":[178],"due":[179],"its":[181],"learning":[183],"capabilities.":[184]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
