Results 151 to 160 of about 27,824 (260)

OPTIMIZING MULTILAYER PERCEPTRON NEURAL NETWORK HYPERPARAMETERS

open access: yesJournal of Process Management and New Technologies
Ivana PETKOVSKI
doaj   +1 more source

Application of GAN–CNN in Risk Assessment of Pipeline Failures in Multiphase Pipeline With Image Information Encoding Approach

open access: yesEnergy Science &Engineering, EarlyView.
Field data from multiphase pipelines are transformed into grayscale images via Image Information Encoding, preserving feature values and interparameter relationships. A GAN–CNN model generates synthetic images that are decoded to expand the original database.
Sihang Chen, Na Zhang, Biyuan Shui
wiley   +1 more source

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

open access: yesEnergy 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   +2 more
wiley   +1 more source

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

open access: yesEnergy 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   +2 more
wiley   +1 more source

Intraday Functional PCA Forecasting of Cryptocurrency Returns

open access: yesJournal 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

Home - About - Disclaimer - Privacy