{"id":"https://openalex.org/W2905453791","doi":"https://doi.org/10.1109/ssd.2018.8570476","title":"A New Strategy for Neural Emulator Learning Rate Tuning","display_name":"A New Strategy for Neural Emulator Learning Rate Tuning","publication_year":2018,"publication_date":"2018-03-01","ids":{"openalex":"https://openalex.org/W2905453791","doi":"https://doi.org/10.1109/ssd.2018.8570476","mag":"2905453791"},"language":"en","primary_location":{"id":"doi:10.1109/ssd.2018.8570476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssd.2018.8570476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 15th International Multi-Conference on Systems, Signals &amp; Devices (SSD)","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/A5030022250","display_name":"Fatma Ezzahra Rhili","orcid":"https://orcid.org/0000-0002-7199-217X"},"institutions":[{"id":"https://openalex.org/I68916915","display_name":"University of Gab\u00e8s","ror":"https://ror.org/022efad20","country_code":"TN","type":"education","lineage":["https://openalex.org/I68916915"]}],"countries":["TN"],"is_corresponding":true,"raw_author_name":"Fatma Ezzahra Rhili","raw_affiliation_strings":["Research Unit: Numerical Control of Industrial Processes (CONPRI), National School of Engineers of Gabes-Tunisia"],"affiliations":[{"raw_affiliation_string":"Research Unit: Numerical Control of Industrial Processes (CONPRI), National School of Engineers of Gabes-Tunisia","institution_ids":["https://openalex.org/I68916915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025631165","display_name":"Asma Atig","orcid":null},"institutions":[{"id":"https://openalex.org/I68916915","display_name":"University of Gab\u00e8s","ror":"https://ror.org/022efad20","country_code":"TN","type":"education","lineage":["https://openalex.org/I68916915"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Asma Atig","raw_affiliation_strings":["Research Unit: Numerical Control of Industrial Processes (CONPRI), National School of Engineers of Gabes-Tunisia"],"affiliations":[{"raw_affiliation_string":"Research Unit: Numerical Control of Industrial Processes (CONPRI), National School of Engineers of Gabes-Tunisia","institution_ids":["https://openalex.org/I68916915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028473969","display_name":"Ridha Ben Abdennour","orcid":null},"institutions":[{"id":"https://openalex.org/I68916915","display_name":"University of Gab\u00e8s","ror":"https://ror.org/022efad20","country_code":"TN","type":"education","lineage":["https://openalex.org/I68916915"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Ridha Ben Abdennour","raw_affiliation_strings":["Research Unit: Numerical Control of Industrial Processes (CONPRI), National School of Engineers of Gabes-Tunisia"],"affiliations":[{"raw_affiliation_string":"Research Unit: Numerical Control of Industrial Processes (CONPRI), National School of Engineers of Gabes-Tunisia","institution_ids":["https://openalex.org/I68916915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5030022250"],"corresponding_institution_ids":["https://openalex.org/I68916915"],"apc_list":null,"apc_paid":null,"fwci":0.5077,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.75141781,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"952","last_page":"957"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9959999918937683,"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/T11236","display_name":"Control Systems and Identification","score":0.995199978351593,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7231964468955994},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4659866690635681},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4026143550872803}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7231964468955994},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4659866690635681},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4026143550872803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssd.2018.8570476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssd.2018.8570476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 15th International Multi-Conference on Systems, Signals &amp; Devices (SSD)","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":21,"referenced_works":["https://openalex.org/W129624237","https://openalex.org/W1530989012","https://openalex.org/W1806891645","https://openalex.org/W1964810584","https://openalex.org/W1982484312","https://openalex.org/W1984205520","https://openalex.org/W1993054357","https://openalex.org/W2002853564","https://openalex.org/W2011771743","https://openalex.org/W2012758998","https://openalex.org/W2016589492","https://openalex.org/W2019028915","https://openalex.org/W2081532446","https://openalex.org/W2085629420","https://openalex.org/W2105028232","https://openalex.org/W2138484437","https://openalex.org/W2139011379","https://openalex.org/W2141745988","https://openalex.org/W2142923542","https://openalex.org/W2160208155","https://openalex.org/W6605324605"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W2350741829","https://openalex.org/W2530322880","https://openalex.org/W1596801655"],"abstract_inverted_index":{"In":[0],"the":[1,51,61,67,81,92,96,103,113],"present":[2],"paper,":[3],"a":[4,38],"real":[5],"time":[6],"recurrent":[7,23],"learning-based":[8],"emulator":[9,17,29,62],"is":[10,18,70,84],"presented":[11],"for":[12,75],"nonlinear":[13,76],"system.":[14,77],"The":[15,26,78,99],"neural":[16,24,28],"developed":[19],"with":[20,91,112],"fully":[21],"connected":[22],"networks.":[25],"instantaneous":[27],"parameters":[30],"adapt":[31],"themselves":[32],"to":[33],"estimate":[34],"dynamical":[35],"behaviors":[36],"using":[37,102],"starting":[39,68,97],"term.":[40,98],"An":[41],"intuitive":[42],"and":[43],"bad":[44],"choice":[45],"of":[46,60,66,80],"this":[47,56,73],"term":[48],"can":[49],"affect":[50],"emulation":[52],"performances.":[53],"To":[54],"overcome":[55],"problem,":[57],"an":[58],"adaptation":[59],"learning":[63],"rate,":[64],"independently":[65],"term,":[69],"proposed":[71,104],"in":[72,89],"work":[74],"effectiveness":[79],"offered":[82],"strategy":[83,105],"illustrated":[85],"through":[86],"numerical":[87],"simulations":[88],"comparison":[90],"method":[93],"based":[94],"on":[95],"obtained":[100,111],"results":[101],"are":[106],"far":[107],"better":[108],"than":[109],"those":[110],"last":[114],"one.":[115]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
