{"id":"https://openalex.org/W4386078222","doi":"https://doi.org/10.1109/access.2023.3307499","title":"Deep Learning-Based Meta-Modeling for Multi-Objective Technology Optimization of Electrical Machines","display_name":"Deep Learning-Based Meta-Modeling for Multi-Objective Technology Optimization of Electrical Machines","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4386078222","doi":"https://doi.org/10.1109/access.2023.3307499"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3307499","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3307499","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10226214.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10226214.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015313070","display_name":"Vivek Parekh","orcid":"https://orcid.org/0000-0002-7818-1468"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technische Universit\u00e4t Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]},{"id":"https://openalex.org/I889804353","display_name":"Robert Bosch (Germany)","ror":"https://ror.org/01fe0jt45","country_code":"DE","type":"company","lineage":["https://openalex.org/I889804353"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Vivek Parekh","raw_affiliation_strings":["Computational Electromagnetics Group, Technische Universität Darmstadt, Darmstadt, Germany","Powertrain Solutions, Mechanical Engineering and Reliability,Robert Bosch GmbH, Stuttgart, Germany"],"raw_orcid":"https://orcid.org/0000-0002-7818-1468","affiliations":[{"raw_affiliation_string":"Computational Electromagnetics Group, Technische Universität Darmstadt, Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]},{"raw_affiliation_string":"Powertrain Solutions, Mechanical Engineering and Reliability,Robert Bosch GmbH, Stuttgart, Germany","institution_ids":["https://openalex.org/I889804353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090321425","display_name":"Dominik Flore","orcid":null},"institutions":[{"id":"https://openalex.org/I889804353","display_name":"Robert Bosch (Germany)","ror":"https://ror.org/01fe0jt45","country_code":"DE","type":"company","lineage":["https://openalex.org/I889804353"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dominik Flore","raw_affiliation_strings":["Powertrain Solutions, Mechanical Engineering and Reliability, Robert Bosch GmbH, Stuttgart, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Powertrain Solutions, Mechanical Engineering and Reliability, Robert Bosch GmbH, Stuttgart, Germany","institution_ids":["https://openalex.org/I889804353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054323051","display_name":"Sebastian Sch\u00f6ps","orcid":"https://orcid.org/0000-0001-9150-0219"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technische Universit\u00e4t Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sebastian Sch\u00f6ps","raw_affiliation_strings":["Computational Electromagnetics Group, Technische Universität Darmstadt, Darmstadt, Germany"],"raw_orcid":"https://orcid.org/0000-0001-9150-0219","affiliations":[{"raw_affiliation_string":"Computational Electromagnetics Group, Technische Universität Darmstadt, Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.8999,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.88069361,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"11","issue":null,"first_page":"93420","last_page":"93430"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10278","display_name":"Electric Motor Design and Analysis","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11159","display_name":"Manufacturing Process and Optimization","score":0.9779999852180481,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/computer-science","display_name":"Computer science","score":0.8168628215789795},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5852372646331787},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5330143570899963},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5173553824424744},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5166404843330383},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.46901291608810425},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"Multi-objective optimization","score":0.45454829931259155},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.4259680509567261},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18951669335365295}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8168628215789795},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5852372646331787},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5330143570899963},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5173553824424744},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5166404843330383},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.46901291608810425},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.45454829931259155},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.4259680509567261},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18951669335365295},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3307499","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3307499","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10226214.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e8d54c81577a4d1e9d607f0df728697f","is_oa":true,"landing_page_url":"https://doaj.org/article/e8d54c81577a4d1e9d607f0df728697f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 93420-93430 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3307499","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3307499","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10226214.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.44999998807907104}],"awards":[{"id":"https://openalex.org/G8769439076","display_name":null,"funder_award_id":"492661287","funder_id":"https://openalex.org/F4320313176","funder_display_name":"Robert Bosch"}],"funders":[{"id":"https://openalex.org/F4320313176","display_name":"Robert Bosch","ror":"https://ror.org/02venad53"},{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386078222.pdf","grobid_xml":"https://content.openalex.org/works/W4386078222.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W289422824","https://openalex.org/W1498436455","https://openalex.org/W1521086728","https://openalex.org/W1522301498","https://openalex.org/W1959608418","https://openalex.org/W2112311198","https://openalex.org/W2126105956","https://openalex.org/W2760881464","https://openalex.org/W2921710869","https://openalex.org/W2948978827","https://openalex.org/W2964545308","https://openalex.org/W2994032337","https://openalex.org/W3113796221","https://openalex.org/W3116743449","https://openalex.org/W3197054198","https://openalex.org/W4221167278","https://openalex.org/W4226214823","https://openalex.org/W4226377670","https://openalex.org/W4249517230","https://openalex.org/W4280600529","https://openalex.org/W4285135129","https://openalex.org/W4296473467","https://openalex.org/W4306148261","https://openalex.org/W4309226941","https://openalex.org/W4312096761","https://openalex.org/W4317617327","https://openalex.org/W4319068603","https://openalex.org/W6631190155","https://openalex.org/W6640963894"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W2140798747","https://openalex.org/W2142844925","https://openalex.org/W2513211214","https://openalex.org/W4240964608","https://openalex.org/W2085577866","https://openalex.org/W1994436307","https://openalex.org/W2198098822","https://openalex.org/W2022485595"],"abstract_inverted_index":{"Optimization":[0],"of":[1,12,33],"rotating":[2],"electrical":[3],"machines":[4],"is":[5,18,105],"both":[6],"time-":[7],"and":[8,49,63,75],"computationally":[9],"expensive.":[10],"Because":[11],"the":[13,31,86,98],"different":[14,41],"parametrization,":[15],"design":[16,100],"optimization":[17,87,96],"commonly":[19],"executed":[20],"separately":[21],"for":[22,115],"each":[23],"machine":[24,42,48],"technology.":[25],"In":[26],"this":[27],"paper,":[28],"we":[29,57],"present":[30],"application":[32],"a":[34,50,59,64,109],"variational":[35],"auto-encoder":[36],"(VAE)":[37],"to":[38,68,108],"optimize":[39],"two":[40],"technologies":[43],"simultaneously,":[44],"namely":[45],"an":[46],"asynchronous":[47],"permanent":[51],"magnet":[52],"synchronous":[53],"machine.":[54],"After":[55],"training,":[56],"employ":[58],"deep":[60,111],"neural":[61],"network":[62],"decoder":[65],"as":[66],"meta-models":[67],"predict":[69],"global":[70],"key":[71],"performance":[72],"indicators":[73],"(KPIs)":[74],"generate":[76],"associated":[77],"new":[78],"designs,":[79],"respectively,":[80],"through":[81],"unified":[82],"latent":[83],"space":[84],"in":[85,97],"loop.":[88],"Numerical":[89],"results":[90],"demonstrate":[91],"concurrent":[92],"parametric":[93],"multi-objective":[94],"technology":[95],"high-dimensional":[99],"space.":[101],"The":[102],"VAE-based":[103],"approach":[104,114],"quantitatively":[106],"compared":[107],"classical":[110],"learning-based":[112],"direct":[113],"KPIs":[116],"prediction.":[117]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2023-08-23T00:00:00"}