{"id":"https://openalex.org/W2985862567","doi":"https://doi.org/10.1109/iisa.2019.8900675","title":"Hyperparameter Optimization of LSTM Network Models through Genetic Algorithm","display_name":"Hyperparameter Optimization of LSTM Network Models through Genetic Algorithm","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2985862567","doi":"https://doi.org/10.1109/iisa.2019.8900675","mag":"2985862567"},"language":"en","primary_location":{"id":"doi:10.1109/iisa.2019.8900675","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iisa.2019.8900675","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","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/A5071851736","display_name":"Nikolaos Gorgolis","orcid":null},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Nikolaos Gorgolis","raw_affiliation_strings":["Computer Science and Informatics,Department University of Patras Patras,Greece","Department University of Patras Patras, Computer Science and Informatics, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Informatics,Department University of Patras Patras,Greece","institution_ids":["https://openalex.org/I174878644"]},{"raw_affiliation_string":"Department University of Patras Patras, Computer Science and Informatics, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046246683","display_name":"Ioannis Hatzilygeroudis","orcid":"https://orcid.org/0000-0002-4036-9369"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Ioannis Hatzilygeroudis","raw_affiliation_strings":["Computer Science and Informatics,Department University of Patras Patras,Greece","Department University of Patras Patras, Computer Science and Informatics, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Informatics,Department University of Patras Patras,Greece","institution_ids":["https://openalex.org/I174878644"]},{"raw_affiliation_string":"Department University of Patras Patras, Computer Science and Informatics, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053867332","display_name":"Zolt\u00e1n Istenes","orcid":"https://orcid.org/0000-0002-0169-4791"},"institutions":[{"id":"https://openalex.org/I106118109","display_name":"E\u00f6tv\u00f6s Lor\u00e1nd University","ror":"https://ror.org/01jsq2704","country_code":"HU","type":"education","lineage":["https://openalex.org/I106118109"]},{"id":"https://openalex.org/I2799978770","display_name":"X-Fab (Germany)","ror":"https://ror.org/030bh9196","country_code":"DE","type":"company","lineage":["https://openalex.org/I2799978770"]}],"countries":["DE","HU"],"is_corresponding":false,"raw_author_name":"Zoltan Istenes","raw_affiliation_strings":["Eötvös Loránd University,Department of Software Technology and Methodology,Budapest,Hungary","Department of Software Technology and Methodology, E\u00f6tv\u00f6s Lor\u00e1nd University, Budapest, Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Eötvös Loránd University,Department of Software Technology and Methodology,Budapest,Hungary","institution_ids":["https://openalex.org/I2799978770"]},{"raw_affiliation_string":"Department of Software Technology and Methodology, E\u00f6tv\u00f6s Lor\u00e1nd University, Budapest, Hungary","institution_ids":["https://openalex.org/I106118109"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044177185","display_name":"Lazlo n Grad Gyenne","orcid":null},"institutions":[{"id":"https://openalex.org/I106118109","display_name":"E\u00f6tv\u00f6s Lor\u00e1nd University","ror":"https://ror.org/01jsq2704","country_code":"HU","type":"education","lineage":["https://openalex.org/I106118109"]},{"id":"https://openalex.org/I2799978770","display_name":"X-Fab (Germany)","ror":"https://ror.org/030bh9196","country_code":"DE","type":"company","lineage":["https://openalex.org/I2799978770"]}],"countries":["DE","HU"],"is_corresponding":false,"raw_author_name":"Lazlo \u2013 Grad Gyenne","raw_affiliation_strings":["Eötvös Loránd University,EIT Digitalv,Budapest,Hungary","EIT Digitalv, E\u00f6tv\u00f6s Lor\u00e1nd University, Budapest, Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Eötvös Loránd University,EIT Digitalv,Budapest,Hungary","institution_ids":["https://openalex.org/I2799978770"]},{"raw_affiliation_string":"EIT Digitalv, E\u00f6tv\u00f6s Lor\u00e1nd University, Budapest, Hungary","institution_ids":["https://openalex.org/I106118109"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5071851736"],"corresponding_institution_ids":["https://openalex.org/I174878644"],"apc_list":null,"apc_paid":null,"fwci":3.7746,"has_fulltext":false,"cited_by_count":77,"citation_normalized_percentile":{"value":0.94766324,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9987999796867371,"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/T10028","display_name":"Topic Modeling","score":0.9987999796867371,"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/T10320","display_name":"Neural Networks and Applications","score":0.9962000250816345,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.9152305126190186},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"Hyperparameter optimization","score":0.8838685750961304},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.77012038230896},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6085302233695984},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5828931331634521},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5398814678192139},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.5130952596664429},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5049708485603333},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.4528050422668457},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.42946675419807434},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3361801505088806},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.09560155868530273},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0899602472782135}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.9152305126190186},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.8838685750961304},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.77012038230896},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6085302233695984},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5828931331634521},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5398814678192139},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5130952596664429},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5049708485603333},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4528050422668457},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.42946675419807434},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3361801505088806},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.09560155868530273},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0899602472782135},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iisa.2019.8900675","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iisa.2019.8900675","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W44465109","https://openalex.org/W1522301498","https://openalex.org/W1591801644","https://openalex.org/W2126321580","https://openalex.org/W2143612262","https://openalex.org/W2250539671","https://openalex.org/W2738180183","https://openalex.org/W2758301081","https://openalex.org/W2760493402","https://openalex.org/W2792795990","https://openalex.org/W2901312569","https://openalex.org/W4294170691"],"related_works":["https://openalex.org/W2953665647","https://openalex.org/W4281646320","https://openalex.org/W4205712847","https://openalex.org/W3169687406","https://openalex.org/W2954882791","https://openalex.org/W4287818966","https://openalex.org/W4388119537","https://openalex.org/W3014750173","https://openalex.org/W3114025147","https://openalex.org/W3192751261"],"abstract_inverted_index":{"Next":[0],"word":[1],"prediction":[2,37],"is":[3,47,61,70,115,123],"an":[4,141],"important":[5],"problem":[6],"in":[7,13],"the":[8,27,40,56,73,76,79,82,109,112,126],"domain":[9],"of":[10,29,55,59,75,98,129],"NLP,":[11],"hence":[12],"modern":[14],"artificial":[15,50],"intelligence.":[16],"It":[17],"draws":[18],"both":[19],"scientific":[20],"and":[21,43,134],"industrial":[22],"interest,":[23],"as":[24],"it":[25,135],"consists":[26],"core":[28],"many":[30],"processes,":[31],"like":[32],"autocorrection,":[33],"text":[34],"generation,":[35],"review":[36],"etc.":[38],"Currently,":[39],"most":[41],"efficient":[42],"common":[44,131],"approach":[45],"used":[46,85,124],"classification,":[48],"using":[49],"neural":[51],"networks":[52],"(ANNs).":[53],"One":[54],"main":[57],"drawbacks":[58],"ANNs":[60],"fine":[62,87],"-":[63,88],"tuning":[64,89,128,137],"their":[65],"hyperparameters,":[66],"a":[67,106,117,130],"procedure":[68],"which":[69,122],"essential":[71],"to":[72,108],"performance":[74],"model.":[77],"On":[78],"other":[80],"hand,":[81],"approaches":[83],"usually":[84],"for":[86,125],"are":[90],"either":[91],"computationally":[92],"unaffordable":[93],"(e.g.":[94,101],"grid":[95],"search)":[96],"or":[97],"uncertain":[99],"efficiency":[100,138],"trial":[102],"&":[103],"error).":[104],"As":[105],"response":[107],"above,":[110],"through":[111],"current":[113],"paper":[114],"presented":[116],"simple":[118],"genetic":[119],"algorithm":[120],"approach,":[121],"hyperparameter":[127],"language":[132],"model":[133],"achieves":[136],"without":[139],"following":[140],"exhaustive":[142],"search.":[143]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":19},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2}],"updated_date":"2026-05-08T15:41:06.802602","created_date":"2025-10-10T00:00:00"}