{"id":"https://openalex.org/W2947589434","doi":"https://doi.org/10.1109/icmech.2019.8722892","title":"Using a Multidimensional Input/Output Neural Network-Regression for Experienced Replay Suitability on Real World Test Bench Data","display_name":"Using a Multidimensional Input/Output Neural Network-Regression for Experienced Replay Suitability on Real World Test Bench Data","publication_year":2019,"publication_date":"2019-03-01","ids":{"openalex":"https://openalex.org/W2947589434","doi":"https://doi.org/10.1109/icmech.2019.8722892","mag":"2947589434"},"language":"en","primary_location":{"id":"doi:10.1109/icmech.2019.8722892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmech.2019.8722892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Mechatronics (ICM)","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/A5041114535","display_name":"Martin Schiele","orcid":null},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Martin Schiele","raw_affiliation_strings":["TU Ilmenau, Fachgebiet Kraftfahrzeugtechnik, Ilmenau, Germany"],"affiliations":[{"raw_affiliation_string":"TU Ilmenau, Fachgebiet Kraftfahrzeugtechnik, Ilmenau, Germany","institution_ids":["https://openalex.org/I119449181"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038301461","display_name":"Klaus Augsburg","orcid":null},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Klaus Augsburg","raw_affiliation_strings":["TU Ilmenau, Fachgebiet Kraftfahrzeugtechnik, Ilmenau, Germany"],"affiliations":[{"raw_affiliation_string":"TU Ilmenau, Fachgebiet Kraftfahrzeugtechnik, Ilmenau, Germany","institution_ids":["https://openalex.org/I119449181"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5041114535"],"corresponding_institution_ids":["https://openalex.org/I119449181"],"apc_list":null,"apc_paid":null,"fwci":0.3198,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61167179,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"550","issue":null,"first_page":"433","last_page":"439"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T12810","display_name":"Real-time simulation and control systems","score":0.9883999824523926,"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/T12127","display_name":"Software System Performance and Reliability","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/computer-science","display_name":"Computer science","score":0.7165491580963135},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.668036937713623},{"id":"https://openalex.org/keywords/regression-testing","display_name":"Regression testing","score":0.6465157866477966},{"id":"https://openalex.org/keywords/test-bench","display_name":"Test bench","score":0.6058297753334045},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.5597509741783142},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5212610363960266},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4812193214893341},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.42452824115753174},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4191790819168091},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.364346981048584},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34046271443367004},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2667243778705597},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0981631875038147},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.090146005153656},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.089304119348526},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.06002247333526611}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7165491580963135},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.668036937713623},{"id":"https://openalex.org/C161821725","wikidata":"https://www.wikidata.org/wiki/Q917415","display_name":"Regression testing","level":5,"score":0.6465157866477966},{"id":"https://openalex.org/C2776266606","wikidata":"https://www.wikidata.org/wiki/Q476482","display_name":"Test bench","level":2,"score":0.6058297753334045},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.5597509741783142},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5212610363960266},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4812193214893341},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.42452824115753174},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4191790819168091},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.364346981048584},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34046271443367004},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2667243778705597},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0981631875038147},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.090146005153656},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.089304119348526},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.06002247333526611},{"id":"https://openalex.org/C186846655","wikidata":"https://www.wikidata.org/wiki/Q3398377","display_name":"Software construction","level":4,"score":0.0},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C149091818","wikidata":"https://www.wikidata.org/wiki/Q2429814","display_name":"Software system","level":3,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmech.2019.8722892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmech.2019.8722892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Mechatronics (ICM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5400000214576721,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W280280400","https://openalex.org/W1835950057","https://openalex.org/W2064675550","https://openalex.org/W2149723649","https://openalex.org/W2158985775","https://openalex.org/W2345083312","https://openalex.org/W2597903990","https://openalex.org/W2605847566","https://openalex.org/W2625614184","https://openalex.org/W2752561458","https://openalex.org/W2762760020","https://openalex.org/W2766447205","https://openalex.org/W4233333560","https://openalex.org/W4250477217","https://openalex.org/W4297810554","https://openalex.org/W4298857966","https://openalex.org/W4300799055","https://openalex.org/W6745190604"],"related_works":["https://openalex.org/W4384302763","https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W2034959125","https://openalex.org/W2355687852"],"abstract_inverted_index":{"The":[0,146],"research":[1],"described":[2],"in":[3,99],"this":[4,150,163],"paper":[5],"focuses":[6],"on":[7,37],"test":[8,11],"bench":[9],"and":[10,39,53,80,92,138,155],"object":[12],"behavior":[13],"-":[14],"regression":[15],"simulation":[16],"for":[17,152],"offline":[18],"machine":[19],"learning":[20,134],"algorithms":[21],"to":[22,43,59,66,86,95,120,129],"be":[23],"trained":[24],"later":[25],"on.":[26],"Scientific":[27],"institutes":[28],"as":[29,31,140,142],"well":[30,141],"the":[32,122],"industrial":[33],"science":[34],"often":[35],"relies":[36],"simulations":[38],"real":[40,101,157],"world":[41,102,158],"tests":[42],"get":[44],"information":[45],"about":[46],"their":[47,89],"subject.":[48],"Both":[49],"technics":[50],"have":[51],"advantages":[52],"disadvantages.":[54],"It":[55],"is":[56,64,118,160],"our":[57],"goal,":[58],"create":[60],"an":[61,71],"agent,":[62],"that":[63],"able":[65],"control":[67],"complex":[68,90],"machines":[69],"like":[70],"automotive":[72],"engine":[73],"or":[74],"a":[75,100],"power":[76],"plant":[77],"by":[78],"itself":[79],"unsupervised.":[81],"Most":[82],"applications":[83],"are":[84],"hard":[85],"simulate":[87],"within":[88],"environment":[91],"not":[93],"fail-save":[94],"train":[96],"while":[97],"working":[98],"setup.":[103],"To":[104],"handle":[105],"this,":[106],"scientists":[107],"from":[108,132],"other":[109],"fields":[110],"invented":[111],"something":[112],"called":[113],"\u201creplay":[114],"memory\u201d.":[115],"This":[116],"technic":[117],"used":[119],"remind":[121],"agent":[123],"of":[124,149,162],"already":[125],"experienced":[126],"data":[127],"repeatedly":[128],"prevent":[130],"it":[131],"just":[133],"recently":[135],"done":[136],"actions":[137],"states":[139],"interpolating":[143],"unseen":[144],"data.":[145],"possible":[147],"usability":[148],"concept":[151],"continuous,":[153],"non-linear":[154],"multidimensional":[156],"problems":[159],"subject":[161],"article.":[164]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
