study methods such as Random Forest, Linear Regression, LSTM, and Bi-LSTM which were employed and evaluated using … performance metrics including Mean Squared Error (MSE), Mean Absolute Error (MAE), and R-Squared. Among these, the Bi-LSTM model …

, we propose a hybrid ANN-LSTM deep learning model optimized with cross-entropy, fuzzy logic, and an attention mechanism to … the feature extraction strength of ANN with the temporal learning of LSTM, while cross-entropy improves convergence, fuzzy …

-term memory (LSTM), and a hybrid CNN-LSTM neural network in predicting real-time forces. The experimental forces predicted by the …

(CNNs), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRUs) to enhance the accuracy and robustness of financial … against standalone CNN, LSTM, and GRU architectures. Experimental results show that the hybrid CNN-LSTM-GRU model achieves … demonstrates faster convergence than LSTM and improved class balance compared to CNN and GRU, reducing false negatives for high …

prices and analyzing returns. Design/methodology/approach - The research applies long short-term memory (LSTM) neural … (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). Findings - LSTM model results produced positive … investors seeking data-driven forecasting in emerging markets should prioritize markets like India and China, where LSTM shows …

performance of Long Short-Term Memory (LSTM) neural networks relative to a TVP-VAR proxy implemented as an expanding window VAR … that the baseline LSTM model delivers modest but more stable error-based performance than the TVP-VAR proxy, with … LSTM forecasts. The attribution analysis highlights recent REIT returns, global equity indicators-particularly the Hang …

. This study proposes a novel CNN-LSTM neural network that can extract potential features from sample data to effectively … conventionally used for prediction. In addition, the proposed model is evaluated against SVR and two different LSTM models. The … predictive accuracy of the model. The CNN-LSTM model, with the inclusion of EPU, IDEMV, and both, achieves a high prediction …