{"date_updated":"2025-11-24T07:36:17Z","article_type":"original","extern":"1","type":"journal_article","author":[{"orcid":"0009-0002-3257-3877","full_name":"Katter, Vincent","id":"239593","last_name":"Katter","first_name":"Vincent","orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0002-3257-3877/work/197573926"},{"orcid":"0000-0002-8362-5369","id":"252434","full_name":"Jaster, Bjarne","first_name":"Bjarne","last_name":"Jaster","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-8362-5369/work/197573927"},{"last_name":"Schöne","first_name":"Marvin","full_name":"Schöne, Marvin","id":"218388"}],"status":"public","volume":2,"publisher":"Hochschule Bielefeld","publication":"Schriftenreihe des Institute for Data Science Solutions","main_file_link":[{"url":"https://journals.hsbi.de/sidas/issue/view/25","open_access":"1"}],"department":[{"_id":"103"}],"year":"2024","_id":"6299","title":"Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme ","abstract":[{"text":"This study investigates the application of Long Short-TermMemory (LSTM) models to approximate complex physical processes. LSTM  models,  which  are  characterized  by  their  ability  to  processlarge  data  sets  and  detect  hidden  patterns,  are  evaluated  for  theirprediction capabilities. The research focuses on the advantages ofLSTM models, such as accurate predictions, as well as challengessuch as data dependency and the risk of overfitting. Experiments ona heating system show that LSTM models with optimized inputs andhyperparameters can be effectively used for predictive maintenanceand   improving   operational   efficiency   in   industrial   applications.Bayesian optimization is used for hyperparameter optimization, whichenables  an  improvement  in  model  accuracy  and  a  reduction  inevaluation time. The results of this optimization and the knowledgegained from it offer valuable insights for the use of LSTM models intechnical and industrial areas.","lang":"eng"}],"language":[{"iso":"ger"}],"citation":{"chicago":"Katter, Vincent, Bjarne Jaster, and Marvin Schöne. “Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme .” <i>Schriftenreihe des Institute for Data Science Solutions</i> 2 (2024). <a href=\"https://doi.org/10.60802/SIDAS.2024.2\">https://doi.org/10.60802/SIDAS.2024.2</a>.","short":"V. Katter, B. Jaster, M. Schöne, Schriftenreihe des Institute for Data Science Solutions 2 (2024).","bibtex":"@article{Katter_Jaster_Schöne_2024, title={Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme }, volume={2}, DOI={<a href=\"https://doi.org/10.60802/SIDAS.2024.2\">10.60802/SIDAS.2024.2</a>}, journal={Schriftenreihe des Institute for Data Science Solutions}, publisher={Hochschule Bielefeld}, author={Katter, Vincent and Jaster, Bjarne and Schöne, Marvin}, year={2024} }","ama":"Katter V, Jaster B, Schöne M. Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme . <i>Schriftenreihe des Institute for Data Science Solutions</i>. 2024;2. doi:<a href=\"https://doi.org/10.60802/SIDAS.2024.2\">10.60802/SIDAS.2024.2</a>","apa":"Katter, V., Jaster, B., &#38; Schöne, M. (2024). Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme . <i>Schriftenreihe des Institute for Data Science Solutions</i>, <i>2</i>. <a href=\"https://doi.org/10.60802/SIDAS.2024.2\">https://doi.org/10.60802/SIDAS.2024.2</a>","alphadin":"<span style=\"font-variant:small-caps;\">Katter, Vincent</span> ; <span style=\"font-variant:small-caps;\">Jaster, Bjarne</span> ; <span style=\"font-variant:small-caps;\">Schöne, Marvin</span>: Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme . In: <i>Schriftenreihe des Institute for Data Science Solutions</i> Bd. 2, Hochschule Bielefeld (2024)","ieee":"V. Katter, B. Jaster, and M. Schöne, “Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme ,” <i>Schriftenreihe des Institute for Data Science Solutions</i>, vol. 2, 2024.","mla":"Katter, Vincent, et al. “Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme .” <i>Schriftenreihe des Institute for Data Science Solutions</i>, vol. 2, Hochschule Bielefeld, 2024, doi:<a href=\"https://doi.org/10.60802/SIDAS.2024.2\">10.60802/SIDAS.2024.2</a>."},"user_id":"263827","publication_status":"published","intvolume":"         2","doi":"10.60802/SIDAS.2024.2","date_created":"2025-11-17T12:29:54Z","oa":"1"}