Stacked LSTM sequence-to-sequence autoencoder with feature selection for daily solar radiation prediction: A review and new modeling results

S Ghimire, RC Deo, H Wang, MS Al-Musaylh… - Energies, 2022 - mdpi.com
We review the latest modeling techniques and propose new hybrid SAELSTM framework
based on Deep Learning (DL) to construct prediction intervals for daily Global Solar …

[HTML][HTML] A comprehensive review on multiple hybrid deep learning approaches for stock prediction

J Shah, D Vaidya, M Shah - Intelligent Systems with Applications, 2022 - Elsevier
Numerous recent studies have attempted to create efficient mechanical trading systems
through the use of machine learning approaches for stock price estimation and portfolio …

MLP-based Learnable Window Size for Bitcoin price prediction

S Rajabi, P Roozkhosh, NM Farimani - Applied Soft Computing, 2022 - Elsevier
Over the past few years, Bitcoin price prediction has been changed to a big challenge for
investors on cryptocurrencies. In this regard, Neural Networks as a strong structure for …

LSTM-ReGAT: A network-centric approach for cryptocurrency price trend prediction

C Zhong, W Du, W Xu, Q Huang, Y Zhao… - Decision Support …, 2023 - Elsevier
Predicting price trends of cryptocurrencies is a challenging task due to the highly speculative
cryptocurrency market. Prior studies mainly investigate predictors such as historical trading …

[HTML][HTML] Hybrid deep CNN-SVR algorithm for solar radiation prediction problems in Queensland, Australia

S Ghimire, B Bhandari, D Casillas-Perez… - … Applications of Artificial …, 2022 - Elsevier
This study proposes a new hybrid deep learning (DL) model, the called CSVR, for Global
Solar Radiation (GSR) predictions by integrating Convolutional Neural Network (CNN) with …

[HTML][HTML] Deep learning CNN-LSTM-MLP hybrid fusion model for feature optimizations and daily solar radiation prediction

S Ghimire, RC Deo, D Casillas-Pérez, S Salcedo-Sanz… - Measurement, 2022 - Elsevier
Global solar radiation (GSR) prediction plays an essential role in planning, controlling and
monitoring solar power systems. However, its stochastic behaviour is a significant challenge …

State-of-the-art in 1d convolutional neural networks: A survey

AO Ige, M Sibiya - IEEE Access, 2024 - ieeexplore.ieee.org
Deep learning architectures have brought about new heights in computer vision, with the
most common approach being the Convolutional Neural Network (CNN). Through CNN …

Water quality prediction in the luan river based on 1-drcnn and bigru hybrid neural network model

J Yan, J Liu, Y Yu, H Xu - Water, 2021 - mdpi.com
The current global water environment has been seriously damaged. The prediction of water
quality parameters can provide effective reference materials for future water conditions and …

[HTML][HTML] Models used to characterise blockchain features. A systematic literature review and bibliometric analysis

JJ Rico-Pena, R Arguedas-Sanz, C Lopez-Martin - Technovation, 2023 - Elsevier
Blockchain has emerged as an innovative technology with potential to transform business
management, through operational efficiency improvements. Nevertheless, several …

Deep learning for Bitcoin price direction prediction: models and trading strategies empirically compared

O Omole, D Enke - Financial Innovation, 2024 - Springer
This paper applies deep learning models to predict Bitcoin price directions and the
subsequent profitability of trading strategies based on these predictions. The study …