Traditional LSTM vs BiLSTM with an attention mechanism.

<p>Traditional LSTM vs BiLSTM with an attention mechanism.</p>

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Bibliographic Details
Main Author:	Riaz Ud Din (21101290) (author)
Other Authors:	Salman Ahmed (55715) (author), Saddam Hussain Khan (21101293) (author), Abdullah Albanyan (21101296) (author), Julian Hoxha (21101299) (author), Bader Alkhamees (21101302) (author)
Published:	2025
Subjects:	Sociology Science Policy Plant Biology Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified varied prediction space thereby enhancing interpretability requires innovative algorithms necessitate advanced techniques influential features based dynamic financial landscapes directional long short daily closing price speculative market trends ensemble regression framework 45 %, 53 volatile bitcoin market xde framework presents xde framework involves xde framework integrates speculative stock bitcoin customized bilstm leverages 37 %, mae novel attention mechanism customized bilstm models novel framework xde framework customized bilstm speculative nature 32 %, customized bi art models yahoo finance xgboost models theoretical expectations term memory represents improvements performing attention learning capabilities informed decision individual attention generalization capabilities empirical validation demonstrates effectiveness dataset sourced approximately 27 actual errors 2023 ).
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