Researchers have developed a new AI-based method for predicting optical transceiver failures in the computer clusters used for AI training. The new technology could allow operators to anticipate ...
Li, G. , Wei, G. and Xi, Z. (2026) UWB NLOS Signal Recognition Based on Deep Learning. Open Journal of Applied Sciences, 16, 779-797. doi: 10.4236/ojapps.2026.163048 .
As electric vehicles (EVs) surge in popularity to combat climate change and reduce fossil fuel dependence, ensuring the ...
Read more about AI-driven air quality system promises faster, more reliable urban health warnings on Devdiscourse ...
Read more about From disease detection to biomass forecasting: AI improves aquaculture risk strategy on Devdiscourse ...
ABSTRACT: Forecasting fuel prices is a critical endeavor in energy economics, with significant implications for policy formulation, market regulation, and consumer decision-making. This study ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In contrast, data-driven methods do not rely on fixed models or ...
Abstract: In this paper, we propose an option-based deep reinforcement learning (DRL) algorithm called option-critic with long short-term memory (OC-LSTM), which combines the option-critic (OC) ...
Abstract: Energy stock price prediction is a pivotal challenge in financial forecasting, characterized by high volatility and complexity influenced by geopolitical factors, regulatory shifts, and ...
With the rapid development of Industrial Internet of Things (IIoT) technology, various IIoT devices are generating large amounts of industrial sensor data that are spatiotemporally correlated and ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results