A Comprehensive Review of Swarm-Based Meta-Heuristic Algorithms for Optimizing LSTM Networks in Time Series Forecasting

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A Comprehensive Review of Swarm-Based Meta-Heuristic Algorithms for Optimizing LSTM Networks in Time Series Forecasting

Time series forecasting, a critical task in various domains, has seen significant advancements with the emergence of deep learning models like Long Short-Term Memory (LSTM) networks. These models excel at capturing temporal dependencies within data, but their performance is highly sensitive to hyper...

書誌詳細
出版年:	2024 IEEE 22nd Student Conference on Research and Development, SCOReD 2024
第一著者:	2-s2.0-85219566544
フォーマット:	Conference paper
言語:	English
出版事項:	Institute of Electrical and Electronics Engineers Inc. 2024
オンライン･アクセス:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85219566544&doi=10.1109%2fSCOReD64708.2024.10872714&partnerID=40&md5=db119bc7faddf60dcc79a8f7307e1a73

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