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 +2 more
wiley +1 more source
Fast and accurate prediction of adsorption energy of AgPd nanoalloys by deep learning potentials and neural networks. [PDF]
Zhang W +5 more
europepmc +1 more source
Energy Consumption and CO2 Emissions Forecasting of Transport Sector Using Machine Learning
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 +2 more
wiley +1 more source
RMIS-Net: a fast medical image segmentation network based on multilayer perceptron. [PDF]
Zhang B, Xu G, Xing Y, Li N, Li D.
europepmc +1 more source
Triboelectric nanogenerators for vehicle intelligent cockpits
Converting mechanical stimuli from drivers and vehicle motion into electrical signals, triboelectric nanogenerators provide promising interfaces toward passive, flexible, distributed and intelligent sensing for next‐generation automotive cockpits to support three core functional dimensions: driver state monitoring, vehicle state monitoring, and human ...
Haiqiu Tan +9 more
wiley +1 more source
Portable and Digital MOX Sensor Electronic Nose with Thermal Modulation: Design, Stability Analysis, and Long-Term Validation. [PDF]
González V +3 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
Advanced predictive modeling of municipal solid waste management using robust machine learning. [PDF]
Chau KY +3 more
europepmc +1 more source
Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly +2 more
wiley +1 more source
A comparative study of various statistical and machine learning models for predicting restaurant demand in Bangladesh. [PDF]
Hossain MS, Parvin F.
europepmc +1 more source

