Predicting trajectories of coastal area vessels with a lightweight Slice-Diff self attention DOI Creative Commons
Jinxu Zhang, Jin Liu,

Xiliang Zhang

et al.

Complex & Intelligent Systems, Journal Year: 2025, Volume and Issue: 11(5)

Published: April 12, 2025

Language: Английский

Near-lossless EEG signal compression using a convolutional autoencoder: Case study for 256-channel binocular rivalry dataset DOI

Martin Kukrál,

Duc Thien Pham, Josef Kohout

et al.

Computers in Biology and Medicine, Journal Year: 2025, Volume and Issue: 189, P. 109888 - 109888

Published: March 5, 2025

Language: Английский

Citations

0

Deep learning network for predicting the remaining useful life of lithium-ion batteries using the positive and negative convolution perceptron model DOI
Gwi-Man Bak, Young-Chul Bae

Journal of the Chinese Institute of Engineers, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 13

Published: March 14, 2025

Language: Английский

Citations

0

CLAM: A Synergistic Deep Learning Model for Multi-Step Stock Trend Forecasting DOI Creative Commons
Anh Q. Nguyen,

Truong Gia Hy

Intelligenza Artificiale, Journal Year: 2025, Volume and Issue: unknown

Published: March 20, 2025

This paper introduces CLAM, a hybrid deep learning framework that integrates CNNs, LSTMs, and Attention Mechanism (AM) for straightforward multi-step stock trend forecasting. By leveraging CNNs spatial feature extraction, LSTMs capturing temporal dependencies, AM dynamically focusing on relevant data, CLAM significantly outperforms traditional models in predictive accuracy. Evaluated diverse datasets from different industries, demonstrates an average reduction of over 80% MAE RMSE compared to standalone CNN, LSTM, fused CNN-LSTM. The model’s ability capture both short-term long-term trends is particularly advantageous real-time financial trading, resulting 75% prediction accuracy, with most cases witnessing consecutive accurate forecasts flash crashes or uptrends, which aids strategic investment decisions risk management. Code data are available at: https://anonymous.4open.science/r/CNN-LSTM-AM-AB13/src/CLAM.ipynb .

Language: Английский

Citations

0

Investigating the Accuracy of Neural Networks for Blood Pressure Prediction in the ICU DOI Creative Commons
Charles J. Gillan,

Bartosz Górecki

Informatics in Medicine Unlocked, Journal Year: 2025, Volume and Issue: unknown, P. 101635 - 101635

Published: March 1, 2025

Language: Английский

Citations

0

Predicting trajectories of coastal area vessels with a lightweight Slice-Diff self attention DOI Creative Commons
Jinxu Zhang, Jin Liu,

Xiliang Zhang

et al.

Complex & Intelligent Systems, Journal Year: 2025, Volume and Issue: 11(5)

Published: April 12, 2025

Language: Английский

Citations

0