Deep learning for cybersecurity in smart grids: Review and perspectives
Protecting cybersecurity is a non‐negotiable task for smart grids (SG) and has garnered
significant attention in recent years. The application of artificial intelligence (AI), particularly …
significant attention in recent years. The application of artificial intelligence (AI), particularly …
[HTML][HTML] A multi-head attention-based transformer model for traffic flow forecasting with a comparative analysis to recurrent neural networks
Traffic flow forecasting is an essential component of an intelligent transportation system to
mitigate congestion. Recurrent neural networks, particularly gated recurrent units and long …
mitigate congestion. Recurrent neural networks, particularly gated recurrent units and long …
MINER: Multi-interest matching network for news recommendation
Personalized news recommendation is an essential technique to help users find interested
news. Accurately matching user's interests and candidate news is the key to news …
news. Accurately matching user's interests and candidate news is the key to news …
Transformer-based forecasting for intraday trading in the Shanghai crude oil market: Analyzing open-high-low-close prices
W Huang, T Gao, Y Hao, X Wang - Energy Economics, 2023 - Elsevier
The Shanghai crude oil futures market exudes distinct speculative attributes, underscoring
the pivotal significance of precise price forecasts. Accurate forecasting of Shanghai crude oil …
the pivotal significance of precise price forecasts. Accurate forecasting of Shanghai crude oil …
A novel XGBoost-based featurization approach to forecast renewable energy consumption with deep learning models
For energy suppliers, forecasting the energy demand with accuracy is essential. The current
studies in the literature have employed various statistical and machine/deep learning …
studies in the literature have employed various statistical and machine/deep learning …
Compact convolutional neural network with multi-headed attention mechanism for seizure prediction
X Ding, W Nie, X Liu, X Wang, Q Yuan - International Journal of …, 2023 - World Scientific
Epilepsy is a neurological disorder related to frequent seizures. Automatic seizure prediction
is crucial for the prevention and treatment of epilepsy. In this paper, we propose a novel …
is crucial for the prevention and treatment of epilepsy. In this paper, we propose a novel …
STTEWS: A sequential-transformer thermal early warning system for lithium-ion battery safety
The internal reactions of lithium-ion batteries are susceptible to temperature, which makes
the temperature of significant impact on their safety and performance. Therefore, it is very …
the temperature of significant impact on their safety and performance. Therefore, it is very …
A mathematical interpretation of autoregressive generative pre-trained transformer and self-supervised learning
M Lee - Mathematics, 2023 - mdpi.com
In this paper, we present a rigorous mathematical examination of generative pre-trained
transformer (GPT) models and their autoregressive self-supervised learning mechanisms …
transformer (GPT) models and their autoregressive self-supervised learning mechanisms …
A novel featurization methodology using JaGen algorithm for time series forecasting with deep learning techniques
Accurate time series forecasting is crucial in various fields, including finance, economics,
healthcare, transportation, and energy. Recently, deep learning methods have gained …
healthcare, transportation, and energy. Recently, deep learning methods have gained …
Multi-expert attention network for long-term dam displacement prediction
Y Zhou, T Bao, G Li, X Shu, Y Li - Advanced Engineering Informatics, 2023 - Elsevier
Monitoring and predicting the dam displacement of concrete dams has attracted increasing
attention for ensuring the long-term health conditions. Most existing models focus on just …
attention for ensuring the long-term health conditions. Most existing models focus on just …