{"id":"https://openalex.org/W4385143202","doi":"https://doi.org/10.1007/978-3-031-37940-6_39","title":"Employing a Novel Metaheuristic Algorithm to Optimize an LSTM Model: A Case Study of Stock Market Prediction","display_name":"Employing a Novel Metaheuristic Algorithm to Optimize an LSTM Model: A Case Study of Stock Market Prediction","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4385143202","doi":"https://doi.org/10.1007/978-3-031-37940-6_39"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-031-37940-6_39","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-031-37940-6_39","pdf_url":null,"source":{"id":"https://openalex.org/S2764900261","display_name":"Communications in computer and information science","issn_l":"1865-0929","issn":["1865-0929","1865-0937"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Computer and Information Science","raw_type":"book-chapter"},"type":"book-chapter","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/A5021358227","display_name":"Amin Karimi Dastgerdi","orcid":"https://orcid.org/0000-0002-9404-2492"},"institutions":[{"id":"https://openalex.org/I113456305","display_name":"Leuphana University of L\u00fcneburg","ror":"https://ror.org/02w2y2t16","country_code":"DE","type":"education","lineage":["https://openalex.org/I113456305"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Amin Karimi Dastgerdi","raw_affiliation_strings":["Leuphana University of Lueneburg, 21335, Lueneburg, Germany"],"affiliations":[{"raw_affiliation_string":"Leuphana University of Lueneburg, 21335, Lueneburg, Germany","institution_ids":["https://openalex.org/I113456305"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035867976","display_name":"Paolo Mercorelli","orcid":"https://orcid.org/0000-0003-3288-5280"},"institutions":[{"id":"https://openalex.org/I113456305","display_name":"Leuphana University of L\u00fcneburg","ror":"https://ror.org/02w2y2t16","country_code":"DE","type":"education","lineage":["https://openalex.org/I113456305"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Paolo Mercorelli","raw_affiliation_strings":["Leuphana University of Lueneburg, 21335, Lueneburg, Germany"],"affiliations":[{"raw_affiliation_string":"Leuphana University of Lueneburg, 21335, Lueneburg, Germany","institution_ids":["https://openalex.org/I113456305"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5035867976"],"corresponding_institution_ids":["https://openalex.org/I113456305"],"apc_list":null,"apc_paid":null,"fwci":2.1928,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.89020247,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"478","last_page":"489"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9983000159263611,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.9944000244140625,"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/stock-market-prediction","display_name":"Stock market prediction","score":0.7518836259841919},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.733535885810852},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.6404210925102234},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6385278105735779},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5352051854133606},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.5188554525375366},{"id":"https://openalex.org/keywords/profit","display_name":"Profit (economics)","score":0.4923139810562134},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4839799404144287},{"id":"https://openalex.org/keywords/stock-price","display_name":"Stock price","score":0.47650566697120667},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4502236545085907},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.42617231607437134},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.42293286323547363},{"id":"https://openalex.org/keywords/optimization-algorithm","display_name":"Optimization algorithm","score":0.415946364402771},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.37311577796936035},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3205971121788025},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.31432199478149414},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.15895012021064758},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.12019726634025574},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07851758599281311},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07736051082611084}],"concepts":[{"id":"https://openalex.org/C2776256503","wikidata":"https://www.wikidata.org/wiki/Q7617906","display_name":"Stock market prediction","level":4,"score":0.7518836259841919},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.733535885810852},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.6404210925102234},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6385278105735779},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5352051854133606},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.5188554525375366},{"id":"https://openalex.org/C181622380","wikidata":"https://www.wikidata.org/wiki/Q26911","display_name":"Profit (economics)","level":2,"score":0.4923139810562134},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4839799404144287},{"id":"https://openalex.org/C2988984586","wikidata":"https://www.wikidata.org/wiki/Q1020013","display_name":"Stock price","level":3,"score":0.47650566697120667},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4502236545085907},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.42617231607437134},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.42293286323547363},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.415946364402771},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.37311577796936035},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3205971121788025},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.31432199478149414},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.15895012021064758},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.12019726634025574},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07851758599281311},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07736051082611084},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C2780762169","wikidata":"https://www.wikidata.org/wiki/Q5905368","display_name":"Horse","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/978-3-031-37940-6_39","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-031-37940-6_39","pdf_url":null,"source":{"id":"https://openalex.org/S2764900261","display_name":"Communications in computer and information science","issn_l":"1865-0929","issn":["1865-0929","1865-0937"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Computer and Information Science","raw_type":"book-chapter"},{"id":"pmh:oai:pure.leuphana.de:openaire_cris_publications/55a463d5-b736-4896-95ea-7fd99f1414f1","is_oa":false,"landing_page_url":"http://fis.leuphana.de/de/publications/employing-a-novel-metaheuristic-algorithm-to-optimize-an-lstm-model(55a463d5-b736-4896-95ea-7fd99f1414f1).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400489","display_name":"Multilingual Matters (Channel View Publications)","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Dastgerdi, A K & Mercorelli, P 2023, Employing a Novel Metaheuristic Algorithm to Optimize an LSTM Model : A Case Study of Stock Market Prediction. in M Singh, V Tyagi, P K Gupta, J Flusser & T \u00d6ren (eds), Advances in Computing and Data Sciences : 7th International Conference, ICACDS 2023, Kolkata, India, April 27\u201328, 2023, Revised Selected Papers. Communications in Computer and Information Science, vol. 1848, Springer International Publishing, Cham, pp. 478-489, International Conference on Advances in Computing and Data Sciences, Kolkata, India, 27.04.23. https://doi.org/10.1007/978-3-031-37940-6_39","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pure.leuphana.de:publications/55a463d5-b736-4896-95ea-7fd99f1414f1","is_oa":false,"landing_page_url":"http://fox.leuphana.de/portal/de/publications/employing-a-novel-metaheuristic-algorithm-to-optimize-an-lstm-model(55a463d5-b736-4896-95ea-7fd99f1414f1).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400489","display_name":"Multilingual Matters (Channel View Publications)","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Dastgerdi, A K & Mercorelli, P 2023, Employing a Novel Metaheuristic Algorithm to Optimize an LSTM Model : A Case Study of Stock Market Prediction. in M Singh, V Tyagi, P K Gupta, J Flusser & T \u00d6ren (eds), Advances in Computing and Data Sciences : 7th International Conference, ICACDS 2023, Kolkata, India, April 27\u201328, 2023, Revised Selected Papers. Communications in Computer and Information Science, vol. 1848, Springer International Publishing, Cham, pp. 478-489, International Conference on Advances in Computing and Data Sciences, Kolkata, India, 27.04.23. https://doi.org/10.1007/978-3-031-37940-6_39","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1815264562","https://openalex.org/W2064675550","https://openalex.org/W2255466643","https://openalex.org/W2568461282","https://openalex.org/W2568937765","https://openalex.org/W2728943311","https://openalex.org/W2784246028","https://openalex.org/W2807541381","https://openalex.org/W2883800310","https://openalex.org/W2895790973","https://openalex.org/W2912614123","https://openalex.org/W2945800207","https://openalex.org/W2954397248","https://openalex.org/W3015228848","https://openalex.org/W3016597555","https://openalex.org/W3041417391","https://openalex.org/W3155398915","https://openalex.org/W4205118762","https://openalex.org/W4229446061","https://openalex.org/W4317725821"],"related_works":["https://openalex.org/W4385280324","https://openalex.org/W2912153778","https://openalex.org/W4387163678","https://openalex.org/W4288108708","https://openalex.org/W2973430807","https://openalex.org/W2984436043","https://openalex.org/W4390245176","https://openalex.org/W2912831041","https://openalex.org/W2890685186","https://openalex.org/W2904359912"],"abstract_inverted_index":null,"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-01-21T23:30:37.877113","created_date":"2025-10-10T00:00:00"}