Results 141 to 150 of about 66,291 (256)

Feasibility of Wind‐Powered Green Hydrogen Production via a Hybrid Graph Neural Network‐Transformer Forecasting Model

Energy Science &Engineering, EarlyView.
ABSTRACT Accurate long‐term wind speed forecasting is pivotal for the strategic planning of renewable energy infrastructure, particularly for assessing the techno‐economic feasibility of wind‐powered green hydrogen facilities. However, capturing the complex spatiotemporal dependencies in climate data remains a significant challenge. This study proposes
Iman Baghaei, Mojtaba Mirhosseini, Alireza Zahedi   +2 more
wiley   +1 more source

A hierarchical Bayesian inference model for volatile multivariate exponentially distributed signals. [PDF]

Front Comput Neurosci
Zhu C, Zhou K, Tang F, Tang Y, Li X, Si B.   +5 more
europepmc   +1 more source

Energy Consumption and CO2 Emissions Forecasting of Transport Sector Using Machine Learning

Energy Science &Engineering, EarlyView.
The transport sector accounts for approximately one‐quarter of Iran's final energy consumption. The energy demand in this sector has the least variation, with petroleum products accounting for more than 85% of the demand. Furthermore, the accelerated growth of energy consumption and the sector's reliance on fossil fuels, which are the main cause of ...
Amir Hossein Akbari, Seyyed Mohammad Hashemi, Meisam Farajollahi   +2 more
wiley   +1 more source

Convergence analysis and application for high-order neural networks based on gradient descent learning algorithm via smooth regularization. [PDF]

Sci Rep
Mohamed KS, Adam A, Mohammed YS, Xiong Y.   +3 more
europepmc   +1 more source

A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios

Journal of Forecasting, EarlyView.
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley   +1 more source

Spectral methods for Neural Integral Equations. [PDF]

Ric Mat
Zappala E.
europepmc   +1 more source

Electricity Price Prediction Using Multikernel Gaussian Process Regression Combined With Kernel‐Based Support Vector Regression

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents a new hybrid model for predicting German electricity prices. The algorithm is based on a combination of Gaussian process regression (GPR) and support vector regression (SVR). Although GPR is a competent model for learning stochastic patterns within data and for interpolation, its performance for out‐of‐sample data is not ...
Abhinav Das, Stephan Schlüter, Lorenz Schneider   +2 more
wiley   +1 more source

Reliable uncertainty estimates in deep learning with efficient Metropolis-Hastings algorithms. [PDF]

Nat Commun
Schmal M, Mäder P.
europepmc   +1 more source

Intraday Functional PCA Forecasting of Cryptocurrency Returns

Journal of Forecasting, EarlyView.
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

Diabetic retinopathy severity detection using an improved Whale optimization algorithm and convolutional Kolmogorov-Arnold network. [PDF]

Front Med (Lausanne)
Dutta AK, Aljarallah NA, Sait ARW.
europepmc   +1 more source