{"id":"https://openalex.org/W6963554854","doi":"https://doi.org/10.21227/ghzw-nq82","title":"Sample Data for Training the ANN model of the ANNVR Control","display_name":"Sample Data for Training the ANN model of the ANNVR Control","publication_year":2025,"publication_date":"2025-03-30","ids":{"openalex":"https://openalex.org/W6963554854","doi":"https://doi.org/10.21227/ghzw-nq82"},"language":"en","primary_location":{"id":"doi:10.21227/ghzw-nq82","is_oa":true,"landing_page_url":"https://doi.org/10.21227/ghzw-nq82","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.21227/ghzw-nq82","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Deng, Xiaojun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Xiaojun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Lee, Noven","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Noven","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Yang, Junxiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Junxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Jiang, Yajie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Yajie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Yang, Yun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7196000218391418},{"id":"https://openalex.org/keywords/inductor","display_name":"Inductor","score":0.678600013256073},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.60589998960495},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5820000171661377},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4512999951839447},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.41589999198913574}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7196000218391418},{"id":"https://openalex.org/C144534570","wikidata":"https://www.wikidata.org/wiki/Q5325","display_name":"Inductor","level":3,"score":0.678600013256073},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.60589998960495},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5820000171661377},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4724999964237213},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4512999951839447},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.41589999198913574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39910000562667847},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3952000141143799},{"id":"https://openalex.org/C148043351","wikidata":"https://www.wikidata.org/wiki/Q4456944","display_name":"Current (fluid)","level":2,"score":0.35249999165534973},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3375999927520752},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.3328999876976013},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28850001096725464},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.28220000863075256}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21227/ghzw-nq82","is_oa":true,"landing_page_url":"https://doi.org/10.21227/ghzw-nq82","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"doi:10.21227/ghzw-nq82","is_oa":true,"landing_page_url":"https://doi.org/10.21227/ghzw-nq82","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"is":[1],"the":[2,25,27,40,47,59,63,69,75,79,83,97,105],"sample":[3],"data":[4],"from":[5],"a":[6],"switched-capacitor":[7,41],"single-input":[8,42],"multiple-output":[9,43],"(SC-SIMO)":[10],"converter,":[11,45],"which":[12,73,100],"can":[13],"be":[14],"utilized":[15],"to":[16,39],"train":[17],"an":[18],"artificial":[19],"neural":[20],"network":[21],"(ANN)":[22],"model.":[23,81],"In":[24],"dataset,":[26],"current":[28],"references":[29,107],"IL3ref,":[30,85],"IL2ref,":[31,86],"IL1ref,":[32],"and":[33,37,46,54],"IL0ref":[34],"are":[35,56,66,74,88,101],"recorded":[36,84],"applied":[38],"(SC-SIMO)&nbsp;":[44],"introduced":[48],"inductor":[49,64,70],"currents":[50,65,71],"IL3,":[51],"IL2,":[52],"IL1,":[53],"IL0":[55],"recorded.":[57],"During":[58],"ANN":[60,80,98],"training":[61],"process,":[62],"considered":[67],"as":[68,90,104],"references,":[72],"four":[76],"inputs":[77],"of":[78,96],"Besides,":[82],"IL1ref":[87],"used":[89],"three":[91],"outputs":[92],"(IL3vref,":[93],"IL2vref,":[94],"IL1vref)":[95],"model,":[99],"also":[102],"called":[103],"virtual":[106],"(VRs).&nbsp;":[108]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}
