Results 231 to 240 of about 22,447 (299)
This paper proposes a decentralized peer‐to‐peer federated learning framework for wind turbine bearing remaining useful life prediction, introducing a virtual client paradigm in which statistical health indicators serve as independent feature‐level clients—enabling privacy‐preserving collaborative prognostics from a single physical asset under ...
Jihene Sidhom +2 more
wiley +1 more source
Multi-objective optimization of gold price forecasting using the pareto alpha-cut technique. [PDF]
Bhavana P.
europepmc +1 more source
We present a smart solar tracking method using artificial intelligence to improve the efficiency of solar panels. Unlike traditional techniques, our system learns and adapts to changing sunlight conditions, ensuring faster and more reliable power generation for real‐world energy needs.
Rida Amine +5 more
wiley +1 more source
A Comprehensive Review of AI‐Powered Energy Systems
The role of Artificial Intelligence (AI) in developing next‐generation energy systems is getting more day by day. Therefore, incorporating AI enables real‐time decision‐making and advanced grid management, which are essential for optimizing the use of intermittent renewable sources like wind and solar power.
Armin Razmjoo +5 more
wiley +1 more source
Addressing lightning and market uncertainties in self-scheduling: A fuzzy-markov approach for smart grids. [PDF]
Benistan IS, Shahbazzadeh MJ, Eslami M.
europepmc +1 more source
ChatGPT in Educational Research: A Case Study of Graduate Students' Use and Ethical Perceptions
ABSTRACT The rise of generative AI, particularly ChatGPT, has transformed academic research, raising both opportunities and ethical concerns. This study examines how graduate students in the education field utilize ChatGPT and their ethical perceptions regarding its use.
Eunseon Lim, Hyunwoong Lee, Yeoran Choi
wiley +1 more source
Theory and simulations of delayed stochastic and deterministic models of prion diseases. [PDF]
Boregowda G +6 more
europepmc +1 more source
Intraday Functional PCA Forecasting of Cryptocurrency Returns
ABSTRACT We study the functional PCA (FPCA) forecasting method in application to functions of intraday returns on Bitcoin. We show that improved interval forecasts of future return functions are obtained when the conditional heteroscedasticity of return functions is taken into account.
Joann Jasiak, Cheng Zhong
wiley +1 more source
TimesNet-BFT: Mitigating Network State Uncertainty in Byzantine Consensus via Deep Temporal Modeling. [PDF]
Wang H, Liu H, Liu Y, Ma H, Gao P.
europepmc +1 more source
Using DSGE and Machine Learning to Forecast Public Debt for France
ABSTRACT Forecasting public debt is essential for effective policymaking and economic stability, yet traditional approaches face challenges due to data scarcity. While machine learning (ML) has demonstrated success in financial forecasting, its application to macroeconomic forecasting remains underexplored, hindered by short historical time series and ...
Emmanouil Sofianos +4 more
wiley +1 more source

